Search Results (1,885)

Multimodal imaging techniques have the potential to enhance the interpretation of histology by offering additional molecular and structural information beyond that accessible through hematoxylin and eosin (H&E) staining alone. Here, we present a quantitative approach for comparing the information content of different image modalities, such as H&E and multimodal imaging. We used a combination of deep learning and radiomics-based feature extraction with different information markers, implemented in Python 3.12, to compare the information content of the H&E stain, multimodal imaging, and the combined dataset. We also compared the information content of individual channels in the multimodal image and of different Coherent Anti-Stokes Raman Scattering (CARS) microscopy spectral channels. The quantitative measurements of information that we utilized were Shannon entropy, inverse area under the curve (1-AUC), the number of principal components describing 95% of the variance (PC95), and inverse power law fitting. For example, the combined dataset achieved an entropy value of 0.5740, compared to 0.5310 for H&E and 0.5385 for the multimodal dataset using MobileNetV2 features. The number of principal components required to explain 95 percent of the variance was also highest for the combined dataset, with 62 components, compared to 33 for H&E and 47 for the multimodal dataset. These measurements consistently showed that the combined datasets provide more information. These observations highlight the potential of multimodal combinations to enhance image-based analyses and provide a reproducible framework for comparing imaging approaches in digital pathology and biomedical image analysis. Full article

This study investigates the influence of carbonation duration and sand-to-powder ratio on the compressive strength and pore structure of recycled cement paste–sand (RCP-S) mortar. Specimens incorporating four different sand contents were subjected to carbonation for 1 and 24 h. Fractal dimensions, ranging from 2.60159 to 3.86742, indicated increased pore complexity with extended carbonation exposure. Mercury intrusion porosimetry (MIP) and scanning electron microscopy (SEM) were employed to characterize pore features, including volume, surface area, and diameter. A Menger sponge-based fractal model was applied to compute the fractal dimensions and investigate their relationships with microstructural parameters and mechanical performance. Results showed that prolonged carbonation markedly reduced macropores and large capillary pores, enhanced fine pore content, and improved overall pore connectivity. Fractal analysis revealed that Segments I and IV exhibited the most significant fractal characteristics. The fractal dimension demonstrated exponential correlations with pore diameter; quadratic relationships—with superior statistical performance—with porosity, surface area, and pore volume; and a power–law relationship with compressive strength. These findings highlight the potential of fractal parameters as effective indicators of pore structure complexity and mechanical performance. This study offers a quantitative basis for optimizing pore structure in recycled cementitious materials, promoting their sustainable application in construction. Full article

The nanoporous structure of coal is crucial for the occurrence and development of coalbed methane (CBM). This study, leveraging the combined characterization of atomic force microscopy (AFM) and Gwyddion software (v2.62), investigated six anthracite samples with varying degrees of metamorphism (R_o = 2.11–3.36%). It revealed the intrinsic relationships between their nanoporous structures, surface morphologies, fractal characteristics, and coalification processes. The research found that as R_o increases, the surface relief of coal decreases significantly, with pore structures evolving from being macropore-dominated to micropore-enriched, and the surface tending towards smoothness. Surface roughness parameters (R_a, R_q) exhibit a negative correlation with R_o. Quantitative data indicate that area porosity, pore count, and shape factor positively correlate with metamorphic grade, while mean pore diameter negatively correlates with it. The fractal dimensions calculated using the variance partition method, cube-counting method, triangular prism measurement method, and power spectrum method all show nonlinear correlations with R_o, moisture (M_ad), ash content (A_ad), and volatile matter (V_daf). Among these, the fractal dimension obtained by the triangular prism measurement method has the highest correlation with R_o, A_ad, and V_daf, while the variance partition method shows the highest correlation with M_ad. This study clarifies the regulatory mechanisms of coalification on the evolution of nanoporous structures and surface properties, providing a crucial theoretical foundation for the precise evaluation and efficient exploitation strategies of CBM reservoirs. Full article

The accurate identification of mosquito species is critical for effective mosquito surveillance and control, especially when presented with morphologically similar species like Aedes aegypti and Aedes sierrensis. Damaged specimens and morphologically similar life stages such as eggs and larvae make it difficult to distinguish Aedes aegypti from Aedes sierrensis using microscopy and taxonomic keys. To address this, the AegySierr.ID-qPCR assay, a multiplex quantitative PCR assay that utilizes single-nucleotide polymorphisms within the mitochondrial cytochrome oxidase subunit I gene, was developed to distinguish between these two species. The assay was tested on DNA extracted from the eggs, larvae, and adults of both species, as well as from environmental DNA (eDNA) collected from natural mosquito reproduction sites. It demonstrated a high diagnostic accuracy across multiple life stages, with a sensitivity exceeding 95% for most groups and specificity exceeding 90%, except for field-collected adult Ae. sierrensis (75%). For eDNA samples, the assay achieved 100% sensitivity and 94% specificity for samples classified as Ae. sierrensis and 91% sensitivity and 86% specificity for Ae. aegypti. A two-graph receiver operating characteristic analysis was also used as an alternate method with which to establish Ct thresholds for interpreting results from unknown samples. The AegySierr.ID-qPCR assay enables the rapid and sensitive identification of Ae. aegypti and Ae. sierrensis from specimens and eDNA, and may be of use in mosquito surveillance programs. Full article

This study focuses on the complex pore structure and pronounced heterogeneity of tight sandstone reservoirs in the Linxing area of the Ordos Basin and develops a multi-scale quantitative characterization approach to investigate the coupling mechanism between pore structure and reservoir properties. Six core samples were selected from the Shiqianfeng Formation (depth interval: 1326–1421 m) for detailed analysis. Cast thin sections and scanning electron microscopy (SEM) experiments were employed to characterize pore types and structural features. Nuclear magnetic resonance (NMR) experiments were conducted to obtain T₂ spectra, which were used to classify bound and movable pores, and their corresponding fractal dimensions were calculated separately. In addition, NMR logging data from the corresponding well intervals were integrated to assess the applicability and consistency of the fractal characteristics at the logging scale. The results reveal that the fractal dimension of bound pores shows a positive correlation with porosity, whereas that of movable pores is negatively correlated with permeability, indicating that different scales of pore structural complexity exert distinct influences on reservoir performance. Mineral composition affects the evolution of pore structures through mechanisms such as framework support, dissolution, and pore-filling, thereby further enhancing reservoir heterogeneity. The consistency between logging responses and experimental observations verifies the regional applicability of fractal analysis. Bound pores dominate within the studied interval, and the vertical variation of the PMF/BVI ratio aligns closely with both the NMR T₂ spectra and fractal results. This study demonstrates that fractal dimension is an effective descriptor of structural characteristics across different pore types and provides a theoretical foundation and methodological support for the evaluation of pore complexity and heterogeneity in tight sandstone reservoirs. Full article

This study advances the understanding of atmospheric microplastic (MPs) exposure across urban (US), suburban (SS), and rural (RS) areas of Madrid, Spain, for the first time. Air pollution from MPs remains an understudied issue with broad implications for environmental and human health. Recent evidence highlights the need for multipoint studies to accurately establish atmospheric exposure to MPs, especially during winter seasons in the city. To address this issue, this work conducted active sampling of ≤10 μm aerosol particles, following EN 12341:2014 standards, during the 2024–2025 winter season. A quantitative innovative method using UV-assisted optical microscopy was applied to assess daily MPs exposure. To trace the potential sources and transport pathways, air mass back trajectories were modelled using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) software. The results showed an average exposure (n = 4) of 80 ± 20; 55 ± 9 and 46 ± 20 MPs·m⁻³·day⁻¹ during the sampling period in US, SS, and RS, respectively; and an average exposure (n = 4) of 61 ± 11 MPs·m⁻³·day⁻¹ throughout the winter period between November and December 2024 and January and February 2025. The polymers detected as constituents of MPs were polystyrene, polyethylene, polymethyl methacrylate, and polyethylene terephthalate, achieving a correct identification ratio of 100% for the detected microplastic particles. The HYSPLIT results showed diffuse sources of MPs, especially local, regional, and oceanic sources, in the US. In contrast, microplastic contributions in SS and RS areas originated from local or regional sources, highlighting the need for advanced studies to identify the sources of emissions and transport routes that converge in the occurrence of microplastics in the areas studied. These results demonstrate the atmospheric exposure to microplastics in the city, justifying the need for specialized studies to define the health impacts associated with the inhalation of these emerging pollutants. The findings of this research provide clear evidence of exposure to atmospheric microplastics in urban, suburban, and rural environments in Madrid, suggesting the need for further specialized research to rigorously assess the potential risks to human health associated with microplastic inhalation by the city’s population. Full article

This work presents a comprehensive evaluation of corrosion progression in DH36 naval steel through the integration of electrochemical impedance spectroscopy (EIS), weight loss, scanning electron microscopy (SEM), and advanced magnetic non-destructive techniques under artificial seawater (ASW, ASTM D1141) and natural marine conditions. Quantitative correlations are established between corrosion layer growth, electrochemical parameters, and magnetic permeability, demonstrating the magnetic sensor’s capacity for the real-time, non-invasive assessment of marine steel degradation. Laboratory exposures reveal a rapid initial corrosion phase with the formation of lepidocrocite and goethite, followed by the densification of the corrosion product layer and a pronounced decline in corrosion rate, ultimately governed by diffusion-controlled kinetics. Notably, changes in magnetic permeability closely track both the thickening of non-magnetic corrosion products and microstructural deterioration, with declining μmax and increased hysteresis widths (FWHM) sensitively indicating evolving surface conditions. A direct comparison with in situ marine immersion at Rafina confirms that the evolution of corrosion morphology and the corresponding magnetic response are further modulated by biofilm development, which exacerbates the attenuation of measured surface permeability and introduces greater variability linked to biological activity. These findings underscore the robustness and diagnostic potential of magnetic non-destructive sensors for the predictive, condition-based monitoring of naval steels, bridging laboratory-controlled observations and complex real-world environments with high quantitative fidelity to corrosion kinetics, phase evolution, and microstructural transformations, thus guiding the strategic deployment of protection and maintenance regimens for naval fleet integrity. Full article

Digital holographic microscopy (DHM) provides numerous advantages, such as noninvasive sample analysis, real-time dynamic detection, and three-dimensional (3D) reconstruction, making it a valuable tool in fields such as biomedical research, cell mechanics, and environmental monitoring. To achieve more accurate and comprehensive imaging, it is crucial to capture detailed information on the microstructure and 3D morphology of samples. Phase processing of holograms is essential for recovering phase information, thus making it a core component of DHM. Traditional phase processing techniques often face challenges, such as low accuracy, limited robustness, and poor generalization. Recently, with the ongoing advancements in deep learning, addressing phase processing challenges in DHM has become a key research focus. This paper provides an overview of the principles behind DHM and the characteristics of each phase processing step. It offers a thorough analysis of the progress and challenges of deep learning methods in areas such as phase retrieval, filtering, phase unwrapping, and distortion compensation. The paper concludes by exploring trends, such as ultrafast 3D holographic reconstruction, high-throughput holographic data analysis, multimodal data fusion, and precise quantitative phase analysis. Full article

Organic matter plays a vital role in shale reservoirs as both a hydrocarbon storage medium and migration pathway. However, the quantitative relationship between the microstructural features of organic matter and the macroscopic mechanical and failure behaviors of shale remains unclear due to rock heterogeneity and opacity. In this study, high-resolution three-dimensional digital core models of shale were reconstructed using Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) imaging. The digital models captured the spatial distribution of silicate minerals, clay minerals, and organic matter. Numerical simulations of uniaxial tensile failure were performed on these models, considering variations in the organic matter volume fraction and fractal dimension. The results indicate that an increased organic matter volume fraction and fractal dimension are associated with lower tensile strength, simpler fracture geometry, and reduced acoustic emission activity. Tensile cracks preferentially initiate at interfaces between minerals with contrasting elastic moduli, especially between organic matter and clay, and then propagate and coalesce under loading. These findings reveal that both the volume fraction and fractal structure of organic matter are reliable predictors of tensile strength and damage evolution in shale. This study provides new microscale insights into shale failure mechanisms and offers guidance for optimizing hydraulic fracturing in organic-rich formations. Full article

Interferometric scattering microscopy (iSCAT) is widely used for label-free tracking of nanoparticles and single molecules. However, its ability to identify small molecules is limited by low imaging contrast blurred with noise. Frame-averaging methods are widely used for reducing background noise but require hundreds of frames to produce a single frame as a trade-off. To address this, we applied a spatial–frequency domain deconvolution algorithm to suppress background noise and amplify the signal for each frame, achieving an improvement of ∼ 3-fold without hardware modification. This enhancement is achieved by compensating for missing information within the optical transfer function (OTF) boundary, while high-frequency components (noise) beyond this boundary are filtered. The resulting deconvolution process provides linear signal amplification, making it ideal for quantitative analysis in mass photometry. Additionally, the localization error is reduced by 20%. Comparisons with traditional denoising algorithms revealed that these methods often extract the side lobes. In contrast, our deconvolution approach preserves signal integrity while enhancing sensitivity. This work highlights the potential of image processing techniques to significantly improve the detection sensitivity of iSCAT for small molecule analysis. Full article

During large-scale pavement construction, the preparation of SBS-modified asphalt typically produces large amounts of harmful fumes. The emergence of deodorants can effectively alleviate the problem of smoke emissions during the asphalt manufacturing process. On the basis of ensuring the original road performance, exploring more suitable dosages and types of deodorant is urgently needed. Five commercial deodorants were evaluated using an asphalt smoke collection system, and UV-visible spectrophotometry (UV) was employed to screen the deodorants based on smoke concentration. Gas chromatography–mass spectrometry (GC-MS) was used to quantitatively analyze changes in harmful smoke components before and after adding two deodorants. Subsequently, the mechanisms of action of the two different types of deodorants were analyzed microscopically using fluorescence microscopy. Finally, the performance of bitumen and asphalt mixtures after adding deodorants was evaluated. The results showed that deodorant A (reactive type) and D (adsorption type) exhibited the best smoke suppression effects, with optimal addition rates of 0.6% and 0.5%, respectively. Deodorant A reduced benzene homologues by nearly 50% and esters by approximately 40%, while deodorant D reduced benzene homologues by approximately 70% and esters by approximately 60%, without producing new toxic gases. Both deodorants had a minimal impact on the basic properties of bitumen and the road performance of asphalt mixtures, with all indicators meeting technical specifications. This research provides a theoretical basis for the effective application of deodorants in the future, truly enabling a transition from laboratory research to large-scale engineering applications in the construction of environmentally friendly roads. Full article

Porcine reproductive and respiratory syndrome virus (PRRSV), an enveloped single-stranded positive-sense RNA virus, poses a significant threat to global swine production. Despite the availability of modified live virus and inactivated vaccines, their limited efficacy and safety concerns highlight the urgent need for novel antiviral therapeutics. This study aimed to investigate the molecular mechanisms by which lycopene inhibits PRRSV replication. Initial assessments confirmed that lycopene did not adversely affect cellular viability, cell cycle progression, or apoptosis. Using fluorescence microscopy, flow cytometry, immunoblotting, quantitative real-time PCR (qRT-PCR), and viral titration assays, lycopene was shown to exhibit potent antiviral activity against PRRSV. Mechanistic studies revealed that lycopene suppresses reactive oxygen species (ROS) production, which is critical for PRRSV proliferation. Additionally, lycopene attenuated PRRSV-induced inflammatory responses, as demonstrated by immunoblotting, ELISA, and qRT-PCR assays. These findings suggest that lycopene inhibits PRRSV replication by modulating ROS levels and mitigating inflammation, offering a promising avenue for the development of antiviral therapeutics. This study provides new insights and strategies for combating PRRSV infections, emphasizing the potential of lycopene as a safe and effective antiviral agent. Full article

Tongue cancer, the most aggressive subtype of oral cancer, presents critical challenges due to the limited number of specialists available and the time-consuming nature of conventional histopathological diagnosis. To address these issues, we developed an intelligent diagnostic system integrating Mueller matrix microscopy with deep learning to enhance diagnostic accuracy and efficiency. Through Mueller matrix polar decomposition and transformation, micro-polarization feature parameter images were extracted from tongue cancer tissues, and purity parameter images were generated by calculating the purity of the Mueller matrices. A multi-stage feature dataset of Mueller matrix parameter images was constructed using histopathological samples of tongue cancer tissues with varying stages. Based on this dataset, the clinical potential of Mueller matrix microscopy was preliminarily validated for histopathological diagnosis of tongue cancer. Four mainstream medical image classification networks—AlexNet, ResNet50, DenseNet121 and VGGNet16—were employed to quantitatively evaluate the classification performance for tongue cancer stages. DenseNet121 achieved the highest classification accuracy of 98.48%, demonstrating its potential as a robust framework for rapid and accurate intelligent diagnosis of tongue cancer. Full article

Asphalt plant reclaimed powder is a common solid waste in road engineering. Reusing reclaimed powder as filler holds significant importance for environmental protection and resource conservation. The key factors affecting the feasibility of reclaimed powder reuse are its acidity/alkalinity and cleanliness. Traditional evaluation methods, such as the methylene blue test and plasticity index, can assess reclaimed powder properties to guide its recycling. However, these methods suffer from inefficiency, strong empirical dependence, and high variability. To address these limitations, this study proposes a rapid and precise evaluation method for reclaimed powder properties based on Fourier transform infrared spectroscopy (FTIR). To do so, five field-collected reclaimed powder samples and four artificial samples were evaluated. Scanning electron microscopy (SEM), X-ray fluorescence spectroscopy (XRF), and X-ray diffraction (XRD) were employed to characterize their microphase morphology, chemical composition, and crystal structure, respectively. Subsequently, FTIR was used to establish correlations between key acidity/alkalinity, cleanliness, and multiple characteristic peak intensities. Representative infrared characteristic peaks were selected, and a quantitative functional group index (Is) was proposed to simultaneously evaluate acidity/alkalinity and cleanliness. The results indicate that reclaimed powder primarily consists of tiny, crushed stone particles and dust, with significant variations in crystal structure and chemical composition, including calcium carbonate, silicon oxide, iron oxide, and aluminum oxide. Some samples also contained clay, which critically influenced the reclaimed powder properties. Since both filler acidity/alkalinity and cleanliness are affected by clay (silicon/carbon ratio determining acidity/alkalinity and aluminosilicate content affecting cleanliness), this study calculated four functional group indices based on FTIR absorption peaks, namely the Si-O-Si stretching vibration (1000 cm⁻¹) and the CO₃²⁻ asymmetric stretching vibration (1400 cm⁻¹). These indices were correlated with conventional testing results (XRF for acidity/alkalinity, methylene blue value, and pull-off strength for cleanliness). The results show that the Is index exhibited strong correlations (R² = 0.89 with XRF, R² = 0.80 with methylene blue value, and R² = 0.96 with pull-off strength), demonstrating its effectiveness in predicting both acidity/alkalinity and cleanliness. The developed method enhances reclaimed powder detection efficiency and facilitates high-value recycling in road engineering applications. Full article

Mitochondria play a crucial role in adapting to fluctuating energy demands, particularly in various heart diseases. In addition to functional analyses such as the measurement of ROS or ATP, analysis of mitochondrial ultrastructure can be used to draw further conclusions about their functions and effects in tissue. In this protocol, we introduce a set of measurements to compare the ultrastructural and functional characteristics of human left ventricular mitochondria, using transmission electron microscopy (TEM). Measured parameters included mean size in µm², elongation, count, percental mitochondrial area in the measuring frame, and a conglomeration score. We also introduce a novel method of defining hydropic mitochondria as a comparable evaluation standard. With this cluster of measurement parameters, we aim to contribute a protocol for studying human mitochondrial morphology, distribution, and functionality. Full article