Search Results (19,294)

Background and Objectives: The Vesical Imaging–Reporting and Data System (VI-RADS) represents a standardized approach for interpreting multiparametric magnetic resonance imaging (mp-MRI) in bladder cancer (BC) evaluation. This systematic review aimed to assess the VI-RADS’ diagnostic performance and interobserver agreement in distinguishing muscle-invasive from non-muscle-invasive BC, a crucial differentiation for treatment planning. Materials and Methods: A systematic literature search was conducted through PubMed, Google Scholar, and Web of Science, over an initial five-year time span, from VI-RADS’ inception (May 2018) to November 2023. Studies reporting VI-RADS’ diagnostic performance with histopathological confirmation and interobserver agreement data were included. The diagnostic accuracy was assessed using sensitivity and specificity, while interobserver agreement was evaluated using Cohen’s κ coefficient. Results: Nine studies comprising 1249 participants met the inclusion criteria. Using a VI-RADS score cutoff of ≥3, the pooled sensitivity and specificity for detecting muscle invasion were 88.2% and 80.6%, respectively. Interobserver agreement showed excellent consistency with a mean κ value of 0.82. Individual study sensitivities ranged from 74.1% to 94.6%, while specificities varied from 43.9% to 96.5%. Conclusions: VI-RADS demonstrates high diagnostic accuracy and excellent interobserver agreement in BC staging, supporting its role as a reliable non-invasive diagnostic tool. However, it should be used as a complementary tool to, not a replacement for, histopathological confirmation. Moreover, the variability in specificity suggests the need for standardized training and interpretation protocols. Clinical correlation and adequate reader experience are essential for optimal implementation. Future integration with pathological data may further enhance its predictive value. Full article

Doping lithium cobalt oxide (LiCoO₂) cathode materials is an effective strategy for mitigating the detrimental phase transitions that occur at high voltages. A deep understanding of the relationships between cycle capacity and the design elements of doped LiCoO₂ is critical for overcoming the existing research limitations. The key lies in constructing a robust and interpretable mapping model between data and performance. In this study, we analyze the correlations between the features and cycle capacity of 158 different element-doped LiCoO₂ systems by using five advanced machine learning algorithms. First, we conducted a feature election to reduce model overfitting through a combined approach of mechanistic analysis and Pearson correlation analysis. Second, the experimental results revealed that RF and XGBoost are the two best-performing models for data fitting. Specifically, the RF and XGBoost models have the highest fitting performance for IC and EC prediction, with R² values of 0.8882 and 0.8318, respectively. Experiments focusing on ion electronegativity design verified the effectiveness of the optimal combined model. We demonstrate the benefits of machine learning models in uncovering the core elements of complex doped LiCoO₂ formulation design. Furthermore, these combined models can be employed to search for materials with superior electrochemical performance and processing conditions. In the future, we aim to develop more accurate and efficient machine learning algorithms to explore the microscopic mechanisms affecting doped layered oxide cathode material design, thereby establishing new paradigms for the research of high-performance cathode materials for lithium batteries. Full article

Bloodstream infection (BSI) is a critical medical emergency associated with a high mortality rate. Rapid and accurate identification of the causative pathogen and the results of antimicrobial susceptibility testing are crucial for initiating appropriate antimicrobial therapy. The aim of this study was to evaluate the performance of a new rapid PCR Molecular Mouse System (MMS) for the identification of Gram-negative bacteria (GNB) and GNB resistance genes directly from a positive blood culture (BC). The validation of these rapid multiplex assays was carried out in a real hospital setting. A total of 80 BSI episodes were included in our study and the results were compared with culture-based methods. BC samples in which GNB had previously been detected microscopically and which originated from different hospital wards were analysed. The MMS GNB identification assay achieved a sensitivity of 98.7% and a specificity of 100% for the covered pathogens. In one BC sample, Klebsiella aerogenes was identified at the family level (Enterobacteriaceae) with MMS. However, in three polymicrobial samples, MMS identified bacteria that were not detected by culture-based methods (Klebsiella pneumoniae, K. aerogenes and Stenotrophomonas maltophilia). MMS also showed excellent overall performance in the detection of GNB resistance markers (100% sensitivity and 100% specificity). The type of extended-spectrum beta-lactamase (ESBL) resistance gene identified correctly with MMS was CTX-M-1/9 (n = 17/20), alone or in combination with SHV-type β-lactamase or with the different types of carbapenemase genes. MMS detected one carbapenemase gene of each type (KPC, NDM and OXA-23) and six OXA-48 genes. In addition, the colistin resistance gene mcr-1 was detected in one positive BC with Escherichia coli (E. coli). The time to result was significantly shorter for MMS than for routine culture methods. A retrospective analysis of the patients’ medical records revealed that a change in empirical antimicrobial therapy would have been made in around half of the patients following the MMS results. These results support the use of MMS as a valuable complement to conventional culture methods for more rapid BSI diagnosis and adjustment of empirical therapy. Full article

Background and Objectives: Endodontic success depends on eliminating infection and creating a durable seal to prevent recontamination. The goal of this study was to assess the impact of different ISO sizes on the obturation quality using two reciprocating single-file systems, WaveOne^® Gold and Procodile^®, in two different canal morphologies. Material and Methods: Overall, 140 root canals from human permanent teeth were randomly assigned to 14 groups based on selected ISO sizes and straight and curved canal curvatures, and the two file systems, WaveOne^® Gold files in ISO sizes 20, 25, and 45, and Procodile^® files in ISO sizes 20, 25, 40, and 45, were employed for canal preparation. These 140 canals were obturated using corresponding gutta-percha points and AH-Plus sealer and the quality of the obturation was assessed after sectioning the roots (apical, middle, coronal third) by evaluating the resulting 420 sections under a digital fluorescence microscope with regard to the proportion of gutta-percha, sealer, and unfilled areas. The results were analyzed using nonparametric tests. Results: For both systems, there was a significant difference in the percentage of gutta-percha-filled areas (PGFA, p < 0.001) and sealer-filled areas (PSFA, p < 0.001 among the different ISO sizes). However, no significant difference was observed in the percentage of unfilled areas (PUA, p = 0.354). ISO 40 demonstrated the best results, with the highest percentage of gutta-percha-filled areas (87%) and the lowest percentages of sealer-filled areas (13%) and voids (0.5%). In contrast, the lowest percentages of gutta-percha filled areas were observed in root canal fillings with ISO 20 (81%) and ISO 25 (81%). Regarding both reciprocating file system sizes, ISO 45 in WaveOne^® Gold and ISO 40 in Procodile^® demonstrated significantly improved (p < 0.05) filling quality, with PGFA of 85% and 87%, respectively. The differences between both systems were not significant. Conclusions: The results presented suggest that larger sizes provide better filling results, especially in the apical region. These results underline the importance of selecting appropriate preparation sizes adjusted to the initial anatomical specifications to optimize root canal obturation and ensure a high quality and durable seal. Full article

Alginate hydrogels are integral to many cell-based models in tissue engineering and regenerative medicine. As a natural biomaterial, the properties of alginates can vary and be widely adjusted through the gelation process, making them versatile additives or bulk materials for scaffolds, microcarriers or encapsulation matrices in tissue engineering and regenerative medicine. The requirements for alginates used in biomedical applications differ significantly from those for technical applications. Particularly, the generation of novel niches for stem cells requires reliable and predictable properties of the resulting hydrogel. Ultra-high viscosity (UHV) alginates possess alginates with special physicochemical properties, and thus far, numerical simulations for the gelation process are currently lacking but highly relevant for future designs of stem cell niches and cell-based models. In this article, the gelation of UHV alginates is studied using a microscopic approach for disc- and sphere-shaped hydrogels. Based on the collected data, a multiphase continuum model was implemented to describe the cross-linking process of UHV alginate polysaccharides. The model utilizes four coupled kinetic equations based on mixture theory, which are solved using finite element software. A good agreement between simulation results and experimental data was found, establishing a foundation for future refinements in the development of an interactive tool for cell biologists and material scientists. Full article

Fractured rock masses are extremely common in geological engineering. In order to improve the stability of surrounding rock under dynamic conditions, new grouting materials and their reinforcement characteristics were studied. In this paper, split Hopkinson pressure bar (SHPB) tests were employed to analyze the dynamic mechanical and failure characteristics of grouted fractured rock with nano-grouting material (nano-grouted fractured rock). Simultaneously, high-speed camera tests were utilized to examine the macroscopic dynamic deformation and failure processes. The following was found: (1) Under a relatively low impact air pressure of 0.1 MPa, the mechanical properties of nano-grouted fractured rock are considerably better than those of traditional cement-based grouted rock. However, when the impact air pressure is increased to 0.3 MPa, the superiority of nano-grouting material diminishes, the possible cause of which is explained from the microscopic point of view. This means the nano-grouting material is more suitable for low-engineering-disturbance conditions (e.g., shield construction). (2) Both for the nano- and superfine cement grouting material, the impact fractures initially emerge at the two ends of the original grouted fracture and form a pair of parallel lines. (3) In comparison with 0.1 MPa, the impact pressure of 0.3 MPa leads to more severe damage to the rock specimen. These findings contribute to a deeper understanding of the behavior of nano-grouted fractured rock under dynamic loading and provide valuable insights for relevant engineering applications in the field of rock mechanics and grouting technology. Full article

Background: Pancreatic ductal adenocarcinoma is an aggressive neoplasm with a complex carcinogenesis process that must be understood through the interactions between tumor cells and tumor microenvironment cells. Methods: This study was retrospective with a chronological extension period of 16 years and included 56 cases of pancreatic ductal adenocarcinoma. This study identified, quantified, and correlated the cells of the tumor immune microenvironment in pancreatic ductal adenocarcinoma with major prognostic factors as well as overall survival, using an extensive panel of immunohistochemical markers. Results: Three tumor immunotypes were identified: subtype A (hot immunotype), subtype B (intermediate immunotype), and subtype C (cold immunotype). Patients with immunotype C exhibit considerably higher rates of both pancreatic fistulas and acute pancreatitis. Immunotypes B and C significantly increased the risk of this complication by factors of 3.68 (p = 0.002) and 3.94 (p = 0.001), respectively. The estimated probabilities of fistula formation for each immunotype are as follows: 2.5% for immunotype A, 25% for immunotype B, and 28% for immunotype C. There was a statistically significant difference in median survival times according to tumor immunotype (p < 0.001). Specifically, patients with immunotype C tumors had a median survival time of only 120.5 days, compared to 553.5 days for those with immunotype A and 331.5 for immunotype B tumors. Conclusions: The identification of the immunotype of pancreatic ductal adenocarcinoma can be a predictive factor for the occurrence of complications such as pancreatic fistula as well as for overall survival. Full article

Layered Double Hydroxide (LDH) coatings were synthesized on as-cast, T4 (solution treatment), and T6 (aging treatment) AZ91 magnesium alloys using a hydrothermal method. XRD (X-Ray Diffraction) and SEM (Scanning Electron Microscope) analyses showed that the large β-phases in as-cast AZ91 initially promoted LDH growth via galvanic corrosion, but later compromised coating integrity. In contrast, T6 and T4 alloys, with refined microstructures, formed uniform and compact LDH coatings. Corrosion resistance was enhanced in T6 and T4 alloys, as evidenced by higher impedance from EIS (Electrochemical Impedance Spectroscopy), and HER (Hydrogen Evolution Reaction) tests, due to the formation of dense LDH layers. Full article

Iron-based oxygen carriers (OCs) have received much attention due to their low costs, high mechanical strengths and high-temperature stabilities in the chemical looping gasification (CLG) of biomass, but their chemical reactivity is very ordinary. Converter steel slags (CSSs) are steelmaking wastes and rich in Fe₂O₃, CaO and MgO, which have good oxidative ability and good stability as well as catalytic effects on biomass gasification. Therefore, the composite OCs prepared by mechanically mixing CSSs with iron-based OCs are expected to be used to increase the hydrogen production in the CLG of biomass. In this study, the catalytic performance of CSS/Fe₂O₃ composite OCs prepared by mechanically mixing CSSs with iron-based OCs on the gasification of brewers’ spent grains (BSGs) were investigated in a tubular furnace experimental apparatus. The results showed that when the weight ratio of the CSSs in composite OCs was 0.5, the relative volume fraction of hydrogen reached the maximum value of 49.1%, the product gas yield was 0.85 Nm³/kg and the gasification efficiency was 64.05%. It could be found by X-ray diffraction patterns and scanning electron microscope characterizations that the addition of CSSs helped to form MgFe₂O₄, which are efficient catalysts for H₂ production. Owing to the large and widely distributed surface pores of CSSs, mixing them with iron-based OCs was beneficial for catalytic steam reforming to produce hydrogen. Full article

At the microscale, the three-dimensional morphological features of contact surfaces have a significant impact on the performance of electrical contacts. This paper aims to reconstruct the microscopic contact state of contact groups and to deeply study the effect of contact morphological features on electrical contact performance. To fully obtain multimodal data such as the three-dimensional micro-morphological features and chemical composition distribution of contact surfaces, this paper proposes a contact surface feature-matching method based on entropy rate superpixel seed point adaptive morphological reconstruction. This method can adaptively retain meaningful seed points while filtering out invalid seed points, effectively solving the problem of over-segmentation in traditional superpixel segmentation method. Experimental results show that the proposed method achieves a segmentation accuracy of 92% and reduces over-segmentation by 30% compared to traditional methods. Subsequently, on the basis of the moving and static contact group difference plane model and the W-M model, this paper constructs a three-dimensional surface fractal contact model with an irregular base. This model has the ability to layer simulate multi-parameter elastic and plastic and to extract fractal parameter point cloud height, which can more accurately reflect the actual contact state of the contact group. The model demonstrates a 15% improvement in contact area prediction accuracy and a 20% reduction in contact resistance estimation error compared to existing models. Finally, this paper compares and verifies the theoretical feasibility of the model, providing a new theoretical contact model for the study of the impact of three-dimensional micro-morphology on the electrical contact reliability. Full article

The viscoelastic behavior of asphalt mixtures is a crucial consideration in the analysis of pavement mechanical responses and structural design. This study aims to elucidate the molecular structure and component evolution trends of polyphosphoric acid (PPA)/styrene butadiene styrene block copolymer (SBS)/styrene butadiene rubber copolymer (SBR) composite modified asphalt (CMA) under rolling thin film oven test (RTFOT) and pressure aging (PAV) conditions, as well as to analyze the viscoelastic evolution of CMA mixtures. First, accelerated aging was conducted in the laboratory through RTFOT, along with PAV tests for 20 h and 40 h. Next, the microscopic characteristics of the binder at different aging stages were explored using Fourier-transform infrared spectroscopy (FTIR) and gel permeation chromatography (GPC) tests. Additionally, fundamental rheological properties and temperature sweep tests were performed to reveal the viscoelastic evolution characteristics of CMA. Ultimately, the viscoelastic properties of CMA mixtures under dynamic loading at different aging stages were clarified. The results indicate that the incorporation of SBS and SBR increased the levels of carbonyl and sulfoxide factors while decreasing the level of long-chain factors, which slowed down the rate of change of large molecule content and reduced the rate of change of LMS by more than 6%, with the rate of change of overall molecular weight distribution narrowing to below 50%. The simultaneous incorporation of SBS and SBR into CMA mixtures enhanced the dynamic modulus in the 25 Hz and −10 °C range by 24.3% (AC-13), 15.4% (AC-16), and reduced the $\phi$ by 55.8% (AC-13), 40% (AC-16). This research provides a reference for the application of CMA mixtures in the repair of pavement pothole damage. Full article

As a typical high-energy-density material, the sensitivity of CL-20 severely limits its application in explosives and propellants. Adjusting its structure at the microscopic level can effectively solve such problems. In this study, a microfluidic recrystallization technique was used to prepare ε-CL-20 with three different particle sizes, with narrow particle size distributions (D₅₀ = 2.77 μm, 17.22 μm and 50.35 μm). The prepared samples had fewer surface defects compared to the raw material. As the particle size decreased, the density of CL-20 increased and its impact sensitivity was significantly reduced. The activation energy of the CL-20 prepared using microfluidic technology increased with increases in particle size. Laser ignition experiments revealed that smaller CL-20 particles had the highest energy release efficiency, while larger particles exhibited a higher energy density and more stable energy release. The combustion performance and safety of CL-20 can be effectively improved by improving the crystal size distribution and surface morphology. Controllable preparation of multiple particle sizes of CL-20 was achieved using microfluidic recrystallization technology, which provides a reference for the preparation of multiple particle sizes of other energetic materials. Full article

The rapid development of Connected and Autonomous Vehicles (CAVs) presents challenges in managing mixed traffic flows. Previous studies have primarily focused on mixed traffic flow involving CAVs and Human-Driven Vehicles (HDVs), or on the combination of trucks and cars. However, these studies have not fully addressed the heterogeneous mixed traffic flow consisting of CAVs and HDVs, including trucks and cars, influenced by varying human driving styles. Therefore, this study investigates the influences of the market penetration rate (MPR) of CAVs, truck proportion, and driving style on operational characteristics in heterogeneous mixed traffic flow. A total of 1105 events were extracted from highD dataset to analyze four car-following types: car-following-car (CC), car-following-truck (CT), truck-following-car (TC), and truck-following-truck (TT). Principal Component Analysis (PCA) and clustering techniques were employed to categorize distinct driving styles, while the Intelligent Driver Model (IDM) was calibrated to represent the various car-following behaviors. Subsequently, microscopic simulations were conducted using the Simulation of Urban Mobility (SUMO) platform to evaluate the impact of CAVs on sustainable traffic operations, including road capacity, stability, safety, traffic oscillations, fuel consumption, and emissions under various traffic conditions. The results demonstrate that CAVs can significantly enhance road capacity, improve emissions, and stabilize traffic flow at high MPRs. For instance, when the MPR increases from 40% to 80%, the road capacity improves by approximately 25%, while stability enhances by approximately 33%. In contrast, higher truck proportions lead to reduced capacity, increased emissions, and decreased traffic flow stability. In addition, an increased proportion of mild drivers reduces capacity, raises emissions per kilometer, and improves stability and safety. However, a high proportion of mild human drivers (e.g., 100% mild drivers) may negatively impact traffic safety when CAVs are present. This study provides valuable insights into evaluating heterogeneous traffic flows and supports the development of future traffic management strategies for more sustainable transportation systems. Full article

This study investigates the properties of diamond-like carbon (DLC) coatings deposited onto a Ti6Al4V titanium alloy using plasma-assisted chemical vapor deposition (PACVD). The research encompasses adhesion tests, hardness, surface characterization, as well as corrosion and tribological evaluations. Artificial saliva was employed as both the lubricating and corrosive medium. Microscopic examination revealed a uniform coating with a thickness of about 3.2 µm. Scratch test results indicated that the deposited DLC coating exhibited superior adhesion, lower frictional resistance, and reduced wear compared to the titanium alloy. The coating deposition increased the hardness of the Ti6Al4V alloy by about 75%. Friction coefficients, measured under dry and lubricated conditions, were approximately 80% lower for the DLC-coated samples. Corrosion studies revealed that both the coated and uncoated surfaces demonstrated typical passive behavior and high corrosion resistance in artificial saliva. For DLC coatings, the corrosion current density and the corrosion rate were reduced by 85%. Microscopic observations of wear tracks following tribological and scratch tests confirmed the inferior wear and scratch resistance of the titanium alloy relative to the DLC coating. Under both dry and lubricated conditions (with artificial saliva), the volumetric wear rate of the titanium alloy was over 90% higher than for the DLC coating. Full article

Pollen is a cornerstone of life for plants. Its durability, adaptability, and complex design are the key factors to successful plant reproduction, genetic diversity, and the maintenance of ecosystems. A detailed study of its chemical composition is important to understand the mechanism of pollen–pollinator interactions, pollination processes, and allergic reactions. In this study, a multimodal approach involving Fourier transform infrared spectrometry (FTIR), direct mass spectrometry with an atmospheric solids analysis probe (ASAP), matrix-assisted laser desorption/ionization (MALDI) and ultra-high-performance liquid chromatography–mass spectrometry (UHPLC-MS) was applied for metabolite profiling. ATR-FTIR provided an initial overview of the present metabolite classes. Phenylpropanoid, lipidic, and carbohydrate structures were revealed. The hydrophobic outer layer of pollen was characterized in detail by ASAP-MS profiling, and esters, phytosterols, and terpenoids were observed. Diacyl- and triacylglycerols and carbohydrate structures were identified in MALDI-MS spectra. The MALDI-MS imaging of lipids proved to be helpful during the microscopic characterization of pollen species in their mixture. Polyphenol profiling and the quantification of important secondary metabolites were performed by UHPLC-MS in context with pollen coloration and their antioxidant and antimicrobial properties. The obtained results revealed significant chemical differences among Magnoliophyta and Pinophyta pollen. Additionally, some variations within Magnoliophyta species were observed. The obtained metabolomics data were utilized for pollen differentiation at the taxonomic scale and provided valuable information in relation to pollen interactions during reproduction and its related applications. Full article