Search Results (34)

Impact of long-term plasma storage on biomarker analysis is critical for ensuring data reliability. Cell-free DNA (cfDNA) epigenetic markers, including 5-hydroxymethylcytosine (5hmC), have emerged for disease detection, prognosis, and treatment response. However, the effects of prolonged storage on 5hmC analysis remain unclear. We evaluated the quantity and quality of cfDNA and 5hmC sequencing analyses in 1070 plasma samples stored for up to 14 years from patients with solid tumors and acute myeloid leukemia (AML) and non-cancer individuals. In long-term stored plasma samples, cfDNA yield remained largely stable; however, uniquely mapped reads (UMRs) from 5hmC sequencing were significantly reduced in solid tumor and control samples. Notably, prolonged plasma storage independently contributed to increased genomic DNA (gDNA) contamination in solid tumor and AML samples and significantly correlated with decreased UMRs in control samples. Across all groups, samples with gDNA contamination exhibited significantly reduced UMRs. Furthermore, gDNA contamination independently compromised cfDNA fragment integrity, decreased sequencing library success in solid tumors, and reduced 5hmC sequencing UMRs across all groups. Therefore, extended plasma storage contributes to increased gDNA contamination, compromising cfDNA and 5hmC sequencing quality. Implementing measures to minimize gDNA contamination in long-term plasma storage is crucial for improving downstream cfDNA analysis reliability. Full article

Pituitary adenylate cyclase-activating polypeptide (PACAP) is a neuropeptide that plays significant regulatory roles in the differentiation of the central nervous system and peripheral organs. A lack of the neuropeptide can lead to abnormalities in long bone development. In callus formation, a possible signaling balance shift in PACAP KO mice has been demonstrated, but Notch signalization, with its potential connection with PACAP 1-38, has not been investigated in ossification. Our main goal was to show connections between PACAP and Notch signaling in osteogenesis. Notch signalization showed an elevation in the long bones of PACAP-gene-deficient mice, and it was also elevated during the PACAP 1-38 treatment of UMR-106 and MC3T3-E1 osteogenic cells. Moreover, the inhibition of Notch signaling was compensated by the addition of PACAP 1-38 in vitro. The inorganic and organic matrix production of UMR-106 cells was increased during PACAP 1-38 treatment under the inhibition of Notch signaling. As a possible common target, the expression and nuclear translocation of NFATc1 transcription factor was increased during the disturbance of PACAP and Notch signaling. Our results indicate a possible synergistic regulation during bone formation by PACAP and Notch signalization. The crosstalk between Notch and PACAP signaling pathways highlights the complexity of bone development and homeostasis. Full article

Background: The use of ex vivo assays associated with biomaterials may allow the short-term visualization of a specific cell type response inserted in a local microenvironment. Blood is the first component to come into contact with biomaterials, providing blood clot formation, being substantial in new tissue formation. Thus, this research investigated the physiological blood clot (PhC) patterns formed in 3D scaffolds (SCAs), based on chitosan and 20% beta-tricalcium phosphate and its effect on osteogenesis. Initially, SCA were inserted for 16 h in rats calvaria defects, and, after that, osteoblasts cells (OSB; UMR-106 lineage) were seeded on the substrate formed. The groups tested were SCA + OSB and SCA + PhC + OSB. Cell viability was checked by MTT and mineralized matrix formation in OSB using alizarin red (ARS). The alkaline phosphatase (ALP) and bone sialoprotein (BSP) expression in OSB was investigated by indirect immunofluorescence (IF). The OSB and PhC morphology was verified by scanning electron microscopy (SEM). Results: The SCA + PhC + OSB group showed greater cell viability (p = 0.0169). After 10 days, there was more mineralized matrix deposition (p = 0.0365) and high ALP immunostaining (p = 0.0021) in the SCA + OSB group. In contrast, BSP was more expressed in OSB seeded on SCA with PhC (p = 0.0033). Conclusions: These findings show the feasibility of using PhC in ex vivo assays. Additionally, its inclusion in the experiments resulted in a change in OSB behavior when compared to in vitro assays. This “closer to nature” environment can completely change the scenario of a study. Full article

Various medical treatments aim to counteract the impact of oxidants on mammalian cells. One such antioxidant is Epigallocatechin-3-gallate (EGCG), an active ingredient in green tea, which has demonstrated protective effects against cellular oxidants like camptothecin (CAMPT). This study examines how EGCG mitigates CAMPT’s effects on UMR cells, focusing on cell proliferation and biophysical parameters. UMR cells were treated with different CAMPT concentrations and incubated for 72 h. Subsequently, cell proliferation and viability were assessed. In a separate experiment, UMR cells were co-treated with CAMPT and varying EGCG concentrations to evaluate EGCG’s ability to mitigate CAMPT’s oxidative effect. Electric Cell–Substrate Impedance Sensing (ECIS) technology was also used to assess the biophysical parameters of CAMPT-treated UMR cells, including cell monolayer resistance, cell spreading, and cell attachment. The results showed a concentration-dependent decrease in cell proliferation for CAMPT-treated UMR cells. However, co-treatment with EGCG reversed CAMPT’s oxidative effects in a concentration-dependent manner. ECIS technology revealed a decrease in biophysical parameters when UMR cells were treated with CAMPT alone. Statistical analysis indicated significant differences with p-values < 0.05. This study suggests that EGCG effectively protects UMR cells from oxidative stress and highlights its potential role in mitigating oxidative stress in mammalian cells. Additionally, the use of ECIS technology validates its application in corroborating the biological effects of CAMPT and EGCG on UMR cells. Full article

Background/Objectives: The rat osteosarcoma cell line UMR-106 is widely used for the study of bone cancer biology but it has not been well characterized with modern genomic methods. Methods: To better understand the biology of UMR-106 cells we used a combination of optical genome mapping (OGM), long-read sequencing nanopore sequencing and RNA sequencing.The UMR-106 genome was compared to a strain-matched Sprague-Dawley rat for variants associated with human osteosarcoma while expression data were contrasted with a public osteoblast dataset. Results: Using the COSMIC database to identify the most affected genes in human osteosarcomas we found somatic mutations in Tp53 and H3f3a. OGM identified a relatively small number of differences between the cell line and a strain-matched control animal but did detect a ~45 Mb block of amplification that included Myc on chromosome 7 which was confirmed by long-read sequencing. The amplified region showed several blocks of non-contiguous rearranged sequence implying complex rearrangements during their formation and included 14 genes reported as biomarkers in human osteosarcoma, many of which also showed increased transcription. A comparison of 5mC methylation from the nanopore reads of tumor and control samples identified genes with distinct differences including the OS marker Cdkn2a. Conclusions: This dataset illustrates the value of long DNA methods for the characterization of cell lines and how inter-species analysis can inform us about the genetic nature underlying mutations that underpin specific tumor types. The data should be a valuable resource for investigators studying osteosarcoma, in general, and specifically the UMR-106 model. Full article

This study innovatively assesses the Mun River flow components in Thailand, integrating artificial neural networks (ANNs) and isotopic (δ¹⁸O) end-member mixing analysis (IEMMA). It quantifies the contributions of the Upper Mun River (UMR) and Chi River (CR) to the overall flow, revealing a discrepancy in their estimated contributions. The ANN method predicts that the UMR and CR contribute approximately 70.5% and 29.5% respectively, while IEMMA indicates a more pronounced disparity with 84% from UMR and 16% from CR. This divergence highlights the distinct perspectives of ANN, focusing on hydrological data patterns, and IEMMA, emphasizing isotopic signatures. Despite discrepancies, both methods validate UMR as a significant contributor to the overall flow, highlighting their utility in hydrological research. The findings emphasize the complexity of river systems and advocate for an integrated approach of river flow analysis for a comprehensive understanding, crucial for effective water resource management and planning. Full article

Wildfires usually lead to a large amount of property damage and threaten life safety. Image recognition for fire detection is now an important tool for intelligent fire protection, and the advancement of deep learning technologies has enabled an increasing number of cameras to possess functionalities for fire detection and automatic alarm triggering. To address the inaccuracies in extracting texture and positional information during intelligent fire recognition, we have developed a novel network called DCP-Net based on UNet, which excels at capturing flame features across multiple scales. We conducted experiments using the Corsican Fire Dataset produced by the “Environmental Science UMR CNRS 6134 SPE” laboratory at the University of Corsica and the BoWFire Dataset by Chino et al. Our algorithm was compared with networks such as SegNet, UNet, UNet++, and PSPNet, demonstrating superior performance across three metrics: mIoU, F1-score, and OA. Our proposed deep learning model achieves the best mIoU (78.9%), F1-score (76.1%), and OA (96.7%). These results underscore the robustness of our algorithm, which accurately identifies complex flames, thereby making a significant contribution to intelligent fire recognition. Therefore, the proposed DCP-Net model offers a viable solution to the challenges of wildfire monitoring using cameras, with hardware and software requirements typical of deep learning setups. Full article

Unreinforced masonry (URM) buildings in historic urban areas of European countries are generally clustered in an aggregate configuration and are often characterized by façade walls mutually interconnected with adjacent ones. As a result, the seismic performance of buildings in an aggregate configuration can be affected by the mutual interaction between the adjacent units. This interaction, often called the aggregate effect, could significantly influence the level of the seismic vulnerability of URM buildings in aggregate configuration toward in-plane and out-of-plane mechanisms, the latter being the object of the present paper. Traditional methods for assessing the seismic vulnerability of URM buildings neglect the interactions between adjacent buildings, potentially underestimating the actual vulnerability. This study aims to derive fragility curves specific for UMR buildings in aggregate configuration and proposes an innovative methodology that introduces the aggregate effect into an analytical approach, previously developed by the authors for isolated URM buildings. The aggregate effect is modeled by accounting for the friction forces arising among adjacent facades during the development of out-of-plane overturning mechanisms by considering different scenarios, based on how façade walls interact with neighboring structures (e.g., whether they are connected to transverse and/or lateral coplanar ones). The proposed approach is applied to a real case study of an Italian historical center. The obtained results demonstrate that the aggregate effect significantly influences the fragility curves of URM buildings arranged in aggregate configurations. This highlights the importance of considering this effect and the usefulness of the proposed approach for large-scale assessments of seismic vulnerability in historic urban areas, contributing to sustainable disaster risk prevention. Full article

Gravity on Earth is of great interest in geodesy, geophysics, and natural resource exploration. Ship-based gravimeters are a widely used instrument for the collection of surface gravity field data in marine regions. However, due to the considerable distance from the sea surface to the seafloor, the spatial resolution of surface gravity data collected from ships is often insufficient to image the detail of seafloor geological structures and to explore offshore natural minerals. Therefore, the development of a mobile underwater gravimetry system is necessary. The GraviMob gravimeter, developed for a moving underwater platform by Geo-Ocean (UMR 6538 CNRS-Ifremer-UBO-UBS), GeF (UR4630, Cnam) and MAPPEM Geophysics, has been tested over the last few years. In this study, we report on the high-resolution gravity measurements from the GraviMob system mounted on an Autonomous Underwater Vehicle, which can measure at depths of up to several kilometres. The dedicated GraviMob underwater gravity measurements were conducted in the Mediterranean Sea in March 2016, with a total of 26 underwater measurement profiles. All these measurement profiles were processed and validated. In a first step, the GraviMob gravity measurements were corrected for temperature based on a linear relationship between temperature and gravity differences. Through repeated profiles, we acquired GraviMob gravity measurements with an estimated error varying from 0.8 to 2.6 mGal with standard deviation after applying the proposed temperature correction. In a second step, the shipborne gravity data were downward continued to the measurement depth to validate the GraviMob measurements. Comparisons between the corrected GraviMob gravity anomalies and downward continued surface shipborne gravity data revealed a standard deviation varying from 0.8 to 3.2 mGal and a mean bias value varying from −0.6 to 0.6 mGal. These results highlight the great potential of the GraviMob system in measuring underwater gravity. Full article

In this article, we explore the role of family-like relationships in creating wellbeing for unaccompanied minor refugees (UMRs) to Europe. Our theoretical point of departure is a relational approach to wellbeing as conceptualized by Sarah C. White. The data comprises interviews with 51 settled UMRs in Finland, Norway, and Scotland, focused on their social networks, and a selection of paired interviews with young people alongside someone they defined as family-like and important for their wellbeing today. Findings illuminate the important role family-like relationships have in meeting the daily needs of young refugees. These relationships are ascribed meaning in the context of young people’s wider networks and ideas of ‘what family should do’. Family-like relationships gain particular importance for UMRs in two different ways: first, the physical absence of the family of origin enforces children and young people’s need to create trusted, reciprocal networks. Second, building family-like relationships is necessary in a new country where UMRs grow up and face new expectations, needs, and opportunities. We argue that relational wellbeing is built in a hybrid ‘third space’. A welfare state should support the wellbeing of UMRs by nurturing welcoming communities and providing UMRs help with building family-like relationships through formal and other support networks. Full article

Background: Scaffold (SCA) functionalization with aptamers (APT) provides adsorption of specific bioactive molecules on biomaterial surfaces. The aim of this study was to observe if SCA enriched with anti-fibronectin APT can favor coagulum (PhC) and osteoblasts (OSB) differentiation. Methods: 20 μg of APT was functionalized on SCA by simple adsorption. For PhC formation, SCAs were inserted into rat calvaria defects for 17 h. Following proper transportation (buffer solution PB), OSBs (UMR-106 lineage) were seeded over PhC + SCAs with and without APT. Cells and PhC morphology, PhC cell population, protein labeling and gene expression were observed in different time points. Results: The APT induced higher alkaline phosphatase and bone sialoprotein immunolabeling in OSB. Mesenchymal stem cells, leukocytes and lymphocytes cells were detected more in the APT group than when scaffolds were not functionalized. Additionally, an enriched and dense fibrin network and different cell types were observed, with more OSB and white blood cells in PhC formed on SCA with APT. The gene expression showed higher transforming growth factor beta 1 (TGF-b1) detection in SCA with APT. Conclusions: The SCA functionalization with fibronectin aptamers may alter key morphological and functional features of blood clot formation, and provides a selective expression of proteins related to osteo differentiation. Additionally, aptamers increase TGF-b1 gene expression, which is highly associated with improvements in regenerative therapies. Full article

Road extraction from high-resolution satellite images has become a significant focus in the field of remote sensing image analysis. However, factors such as shadow occlusion and spectral confusion hinder the accuracy and consistency of road extraction in satellite images. To overcome these challenges, this paper presents a multi-scale fusion-based road extraction framework, HRU-Net, which exploits the various scales and resolutions of image features generated during the encoding and decoding processes. First, during the encoding phase, we develop a multi-scale feature fusion module with upsampling capabilities (UMR module) to capture fine details, enhancing shadowed areas and road boundaries. Next, in the decoding phase, we design a multi-feature fusion module (MPF module) to obtain multi-scale spatial information, enabling better differentiation between roads and objects with similar spectral characteristics. The network simultaneously integrates multi-scale feature information during the downsampling process, producing high-resolution feature maps through progressive cross-layer connections, thereby enabling more effective high-resolution prediction tasks. We conduct comparative experiments and quantitative evaluations of the proposed HRU-Net framework against existing algorithms (U-Net, ResNet, DeepLabV3, ResUnet, HRNet) using the Massachusetts Road Dataset. On this basis, this paper selects three network models (U-Net, HRNet, and HRU-Net) to conduct comparative experiments and quantitative evaluations on the DeepGlobe Road Dataset. The experimental results demonstrate that the HRU-Net framework outperforms its counterparts in terms of accuracy and mean intersection over union. In summary, the HRU-Net model proposed in this paper skillfully exploits information from different resolution feature maps, effectively addressing the challenges of discontinuous road extraction and reduced accuracy caused by shadow occlusion and spectral confusion factors. In complex satellite image scenarios, the model accurately extracts comprehensive road regions. Full article

In this study, an optimized unilateral magnetic resonance sensor with a three-magnet array is presented for assessing the aging of composite insulators in power grids. The sensor’s optimization involved enhancing the static magnetic field strength and the homogeneity of the RF field while maintaining a constant gradient in the direction of the vertical sensor surface and maximizing homogeneity in the horizontal direction. The center layer of the target area was positioned 4 mm from the coil’s upper surface, resulting in a magnetic field strength of 139.74 mT at the center point of the area, with a gradient of 2.318 T/m and a corresponding hydrogen atomic nuclear magnetic resonance frequency of 5.95 MHz. The magnetic field uniformity over a 10 mm × 10 mm range on the plane was 0.75%. The sensor measured 120 mm × 130.5 mm × 76 mm and weighed 7.5 kg. Employing the optimized sensor, magnetic resonance assessment experiments were conducted on composite insulator samples utilizing the CPMG (Carr–Purcell–Meiboom–Gill) pulse sequence. The T₂ distribution provided visualizations of the T₂ decay in insulator samples with different degrees of aging. Full article

Macrophyte (aquatic plant) recovery has occurred in rivers worldwide, but assemblage patterns and habitat requirements are generally not well understood. We examined patterns of species composition and macrophyte abundance in the Upper Mississippi River (UMR), spanning 22 years of monitoring and a period of vegetation recovery. Non-metric multidimensional scaling (NMDS) ordination revealed a gradient of macrophyte abundance and diversity for 25 species, which were associated with water velocity, depth, wind fetch, and water clarity. Three macrophyte genera of ecological and restoration interest (Zizania aquatica, Vallisneria americana, and Sagittaria spp.) occupied different ecological niches. Trends of NMDS values showed that Z. aquatica first co-occurred in shallow areas with Sagittaria spp. but then expanded into deeper, lotic habitats where V. americana often resided. Curve Fit regression analysis identified large areas of significant increases in the relative abundance of V. americana and percent cover of Z. aquatica in several reaches of the UMR from 1998–2019. Sagittaria spp. were more spatiotemporally dynamic, which may indicate specific habitat requirements and sensitivity to environmental gradients. Our analyses showed that these three ecologically important genera are spatiotemporally dynamic but have somewhat predictable habitat associations, which can guide macrophyte management and restoration in the UMR and other large, floodplain rivers. Full article

In this paper, we propose a method of identifying the position of a tethered delivery catheter in a vascular environment, recombining an untethered magnetic robot (UMR) to the tethered delivery catheter, and safely retrieving them from the vascular environment in an endovascular intervention by utilizing a separable and recombinable magnetic robot (SRMR) and a magnetic navigation system (MNS). From images of a blood vessel and a tethered delivery catheter taken from two different angles, we developed a method of extracting the position of the delivery catheter in the blood vessel by introducing dimensionless cross-sectional coordinates. Then, we propose a retrieval method for the UMR by using the magnetic force considering the delivery catheter’s position, suction force, and rotating magnetic field. We used thane MNS and feeding robot to simultaneously apply magnetic force and suction force to the UMR. In this process, we determined a current solution for generating magnetic force by using a linear optimization method. Finally, we conducted in vitro and in vivo experiments to verify the proposed method. In the in vitro experiment, which was in a glass tube environment, by using an RGB camera, we confirmed that the location of the delivery catheter in the glass tube could be recognized within an average error of 0.05 mm in each of the X- and Z-coordinates and that the retrieval success rate was greatly improved in comparison with that in the case without the use of magnetic force. In an in vivo experiment, we successfully retrieved the UMR in the femoral arteries of pigs. Full article