Microscopy Research and Technique最新文献

Renal cell carcinoma is the primary cause of cancer-related mortality, highlighting the importance of early detection and accurate diagnosis. Manual histopathology image classification methods include limitations such as labor effort, time consumption, and interpathologist variations, which can lead to misdiagnosis, especially in the early stages. An autonomous solution based on deep learning is essential to overcome these constraints. However, vision-based models require significant processing resources and data sets, which pose difficulties for low-end infrastructures. In this study, we have described an approach for analyzing histopathology images using a lightweight truncated Fused-MirrorNet model. With its mirrored architecture, we use partial layer freezing and feature fusion approaches to improve performance. In kidney histopathology image analysis, our suggested strategy outperforms existing CNN and vision transformer models in histopathology image classification. We significantly reduced training time while preserving classification accuracy. The proposed model is deployable, scalable, and reproducible, allowing it to be used on low-end devices. Our strategy also makes it easier to create vision-based deep learning models by removing the requirement for sophisticated computational methodologies and procedures. The proposed model and the comparison models were trained and evaluated using histopathology images from two datasets. The experimental results reveal that the proposed model (Fused-MirrorNet) surpassed the performance of state-of-the-art models used for the classification of histopathology images. The proposed model achieves an accuracy of 92.60% and 90.00% in the TCGA kidney and BreakHis datasets, respectively. These findings indicate that the research conducted to develop the suggested model produced favorable outcomes.

The charge transport properties of DNA make it a promising candidate for molecular electronics, yet the in situ dynamic regulation of its conductivity remains challenging. In this study, a conductive atomic force microscopy (C-AFM) system integrated with magnetic field modulation was developed to investigate the real-time conductivity of λ-DNA on Au-coated mica substrates. The results demonstrate that DNA molecular height positively correlates with tunneling current, with single double-stranded DNA (dsDNA) exhibiting a median current of -1.27 pA in the height range of 300 ~ 600 pm, while multi-stranded intertwined DNA fibers showed significantly enhanced conductivity (median current: -3.71 pA). Under a direct current (DC) magnetic field of 15 mT, both DNA forms exhibited suppressed conductivity, attributed to the Lorentz force effect. In contrast, an alternating current (AC) magnetic field (25 MHz) at 3 mT enhanced conductivity, whereas a 6 mT field led to a reduction. These findings provide direct experimental evidence for the real-time magnetic modulation of the transverse tunneling conductance through DNA molecules and offer a noncontact strategy for tuning DNA-based nanoelectronic devices.

In spatial proteomics, multiplexed immunofluorescence (mIF) enables high-plex visualization of protein expression in preserved tissue, offering insights into tumor heterogeneity and the microenvironment. While MACSima and PhenoCycler-Fusion employ distinct strategies, direct comparisons under biologically controlled in vivo conditions remain limited. We applied both platforms to sagittal formalin-fixed, paraffin-embedded (FFPE) sections from an orthotopic xenograft mouse model of human medulloblastoma (MB), featuring leptomeningeal seeding (LMS). These longitudinal sections spanning brain and spinal cord allowed simultaneous assessment of areas with distinct cellular architecture. Fifteen-marker mIF was performed. MACSima utilized MICS technology with MACS iQ View for automated workflows; PhenoCycler-Fusion used a DNA-barcoded antibody system and QuPath for open-ended image processing. Segmentation was evaluated using identical MACSima data. Both platforms enabled high-plex imaging mIF while preserving tissue morphology. DAPI, Ki-67, and Actin were consistently detected across both systems. Ki-67 expression localized to densely packed tumor regions and was also observed in lower-density areas. Analyzing MACSima data, MACS iQ View detected fewer cells but a higher Ki-67 positive rate in dense regions; conversely, QuPath detected more cells but with a lower positivity rate. In low-density areas, both tools yielded similar results. These differences reflect distinct segmentation algorithms and thresholding strategies. This study confirms both platforms support mIF-based spatial proteomic analysis in complex, heterogeneous tissues. However, analysis tools influence quantification. Therefore, standardization of algorithmic settings and additional validation are crucial for precise data interpretation. This research provides practical insights for platform selection in basic, translational, and clinical applications by directly evaluating staining, image acquisition, and analysis pipelines.

This study aimed to evaluate the biological effects of three calcium silicate-based materials-Biodentine XP (BD-XP), TheraCal PT (THPT), and TheraBase Ca (THB)-on human dental pulp stem cells (hDPSCs), focusing on cytocompatibility, immunomodulatory behavior (via IL-6 expression), and odontogenic/mineralization potential compared to control conditions. hDPSCs were cultured with eluates (25%, 50%, 100%) of BD-XP, THPT, and THB. Cytocompatibility was assessed via metabolic activity assay, cell cycle analysis, and cell migration. Morphology and adhesion were examined by SEM, while surface composition was analyzed by EDX. IL-6 secretion was quantified using ELISA. Gene expression of odontogenic/osteogenic markers (ALP, DSPP, RUNX2, COL-1) was analyzed via qRT-PCR at 14 and 21 days. Alizarin Red S staining was used to assess mineralization. Results were compared to unconditioned and osteogenic controls (p < 0.05). All materials exhibited acceptable cytocompatibility. BD-XP promoted the highest cell viability, migration, and adhesion. IL-6 secretion was significantly reduced in all treated groups, most notably with THB. SEM and EDX showed strong cell attachment and calcium-rich surfaces for BD-XP. BD-XP significantly upregulated DSPP and RUNX2 at both time points and COL-1 at day 21. ALP expression was mainly observed in the positive control. BD-XP also showed the greatest mineralized nodule formation. Biodentine XP demonstrated the most favorable biological behavior, showing high cytocompatibility, upregulation of odontogenic markers, and enhanced mineralization. These results highlight its potential for clinical use in vital pulp therapy and regenerative endodontics.

Xanthium sibiricum Patrin ex Widder and Xanthium italicum Moretti are morphologically similar fructus that are frequently misidentified. Xanthium italicum Moretti may possess inherent toxicity, and its adulteration of genuine medicinal materials poses a threat to clinical drug safety. Macroscopic observation and three microscopic techniques including stereo microscope, optical microscope, and 3D X-ray microscope were used for morphological identification of Xanthium sibiricum Patr ex Widder and Xanthium italicum Moretti in this study. 3D X-ray microscopy was applied as a novel tool for non-destructive, high-resolution discrimination of the two taxa. Intact fructus (n = 30 per species) were first screened macroscopically, then examined by stereo microscopy, optical microscopy, and 3D X-ray microscopy (0.3, 0.7, 1.5, 3.5, 18.06, 20.01 μm voxel size, Zeiss Xradia 520 Versa). The results showed that stereo microscopy, optical microscopy, and 3D X-ray microscopy collectively confirm the same conclusion from three distinct physical perspectives: surface topography, internal two-dimensional structure, and internal three-dimensional density distribution. The two Xanthium species differ significantly in burr spine morphology, fructus size and shape, the architecture and distribution of non-glandular and glandular trichomes, cotyledon conformation, and seed-coat cell patterning. In particular, 3D X-ray microscopy clearly resolves internal cotyledon spatial configurations and involucral cavity architectures, which furnishes critical endomorphic characters for taxonomic diagnosis. 3D X-ray microscopy provides unprecedented volumetric contrast of surface spines and internal seed architecture, permitting confident, non-destructive species identification. This study provides a basis for the safe clinical use of Xanthium sibiricum Patrin ex Widder. The frontier of 3D X-ray microscopy in plant systematics offers a novel, rapid, accurate and non-destructive protocol for the discrimination of morphologically elusive species.

Histological analysis is central to biomedical research and diagnostic pathology, yet conventional two-dimensional (2D) sectioning captures only limited aspects of tissue architecture. Critical spatial relationships-such as tumor boundaries, stromal organization, and vascular networks-remain obscured, restricting diagnostic accuracy and biological interpretation. HistoNeRF addresses these limitations by adapting Neural Radiance Fields (NeRF) to reconstruct three-dimensional (3D) tissue volumes from routine histological sections. In this study, 84 toluidine blue (TB)-stained murine ovarian sections were digitized, alignment-corrected, and integrated into volumetric models. Tissue segmentation was performed using a convolutional neural network, while visualization was achieved through an interactive, GPU-accelerated interface. To ensure accessibility and reproducibility, a Python-based graphical application (HistoNeRF GUI) was developed following Human-Computer Interaction (HCI) principles and containerized with Docker, allowing installation-free deployment via Docker Hub. HistoNeRF produced high-fidelity 3D reconstructions (SSIM = 0.92; Dice similarity coefficient = 0.88), enabling expert histologists to better visualize follicular structures, stromal compartments, and vascular elements. The containerized GUI was deployed successfully from Docker Hub, providing immediate access to 3D reconstruction without a complex local setup. By overcoming the inherent constraints of 2D microscopy, HistoNeRF enhances the visualization, interpretability, and reproducibility of histological architecture. The HCI-guided, cross-platform interface supports scalability and rapid adoption in digital pathology workflows. Although validation was limited to murine ovarian tissue and one staining protocol, this framework can be extended across tissue types and clinical datasets. HistoNeRF bridges routine histology and 3D volumetric analysis through accurate, interactive reconstructions that advance diagnostic precision and biomedical research. While demonstrated on 84 serial TB-stained ovarian sections, broader validation across tissues, stains, and pathological conditions remains future work; to support this, we provide a Dockerized, modular pipeline for straightforward extension.

7-ketocholesterol (7KCh), a cytotoxic oxysterol derived from cholesterol oxidation, plays a pivotal role in the progression of lipid-driven inflammatory diseases such as atherosclerosis. Among its pathogenic mechanisms, 7KCh is known to trigger oxiapoptophagy, a unique convergence of oxidative stress, apoptosis and autophagy. While macrophages typically serve as key phagocytic cells for clearing lipid debris, exposure to 7KCh disrupts this homeostatic role, contributing instead to dysfunctional foam cell formation. Despite its clinical relevance, the precise morphological and mechanistic effects of 7KCh on macrophages remain insufficiently characterized. In this study, we investigated the impact of 7KCh on IC-21 macrophages using a comprehensive, multimodal imaging strategy that integrates phase contrast, differential interference contrast (DIC), fluorescence microscopy and quantitative confocal imaging. Exposure to increasing concentrations (2-10 μg/ml) of 7KCh for 24 h revealed distinct morphological alterations, including cytoplasmic vacuolization, disrupted cellular architecture and pronounced lipid accumulation. Oil red O staining confirmed the accumulation of neutral lipids, while functional assays demonstrated impaired pinocytosis and phagocytosis, hallmark features of foam cell transformation. These findings were further supported by molecular analysis indicating induction of pro-inflammatory markers and oxiapoptophagy signatures. Altogether, this work provides novel insight into the cytotoxic and inflammatory transformation of macrophages by 7KCh and highlights the power of advanced microscopy in delineating lipid-induced immune dysfunction. Our imaging-based approach offers a valuable platform for future investigations into oxysterol-mediated pathologies and therapeutic targeting of foam cell dynamics.

Aflatoxin B1 (AFB1), a potent mycotoxin, poses significant health risks to humans and animals, with the kidney emerging as a secondary target organ beyond its well-documented hepatotoxicity. Cytoskeletal components are essential for proper podocyte, mesangial cell morphology, and glomerular function. This study investigated the histopathological and ultrastructural changes induced by AFB1 on renal tissues, focusing on glomerular filtration barriers, renal tubules, interstitial telocytes, and β-tubulin expression. Adult female Wistar rats were administered 250 μg/kg/day of AFB1 for 8 weeks, and kidney tissues were analyzed using toluidine blue staining, transmission electron microscopy (TEM), and immunohistochemistry. AFB1 exposure induced severe glomerular atrophy, thickened Bowman's capsules, widened Bowman's spaces, and tubular epithelial vacuolation. Telocytes exhibited necrotic changes, TEM confirmed podocyte foot process effacement, mitochondrial damage, and autophagic vacuole formation in proximal and distal tubules. Additionally, telocytes displayed fragmented telopodes and nuclear condensation, suggesting impaired tissue repair mechanisms, while immunohistochemistry revealed upregulated β-tubulin expression in glomeruli and tubules, indicating cytoskeletal disruption. These findings highlight AFB1-induced nephrotoxicity through oxidative stress, cytoskeletal remodeling, and interstitial inflammation, which in turn affect the glomerular filtration, underscoring the kidney's vulnerability to mycotoxin exposure. This study provides novel insights into the role of telocytes and β-tubulin dysregulation in AFB1-induced renal injury, offering a foundation for future research on therapeutic interventions.

Nowadays, blood cell segmentation has emerged as a popular solution for diagnosing hematological disorders. For hematological disorder detection, existing techniques face various limitations, including noise, weak edges, and intensity inhomogeneity. To rectify these problems, a novel Residual-Shuffle2DConv-Squeeze Network approach is proposed in this research to enhance the blood cell segmentation for hematological disorder diagnosis. Distinguishing blood cells, overlapped cells segmentation, edge detection, and morphological operations are the different stages of this approach for performing blood cell segmentation. The Residual-Shuffle Global Attention Network is used for morphological feature extraction, and this network integrates the Residual Network and Shuffle Global Attention Network. To retain fine-grained morphological features and capture variations of blood cell structure, the Residual-Shuffle Global Attention Network model is applied. The Shuffle Global Attention Network module has ShuffleNet and the Global Attention Mechanism. The ShuffleNet reduces the computational cost, and the Global Attention Mechanism helps to preserve crucial features through various layers. Finally, the 2DConv-SNN is applied to detect and classify hematological disorders. The comprehensive experiments are conducted on different datasets, including the Sickle Cell Disease Dataset and the Acute Lymphoblastic Leukemia dataset. The experimental results showcased that the Residual-Shuffle2DConv-Squeeze Network approach enhanced the detection of the hematological disorder with an accuracy of 98.69%, a dice coefficient of 97.05% and a Jaccard index of 96.43% respectively.

Visualization of neuronal ultrastructure facilitates molecular and biochemical analyses that may help to better elucidate neural function and information processing. While the neuron exists at the micron scale, critical events such as synaptic vesicle release and dendritic spine remodeling occur at the nanometer scale, necessitating submicron resolution. Scanning electron microscopy (SEM) provides high-resolution imaging at these scales. However, the commonly used dehydration-based sample preparation method induces morphological distortions, while environmental SEM requires specialized equipment that is costly and difficult to operate. The NanoSuit method has recently emerged as a promising alternative, enabling SEM observations under high-vacuum conditions without standard (dehydration-based) pretreatment. Although known to be successful when applied to specimens with protective surface layers such as insects, flowers, and wet tissues, its effectiveness when examining "bare" cultured cells has not been thoroughly explored. Here, we present a modified NanoSuit protocol for SEM examination of cultured neurons and compare it with standard pretreatment. We demonstrate that traditional methods frequently cause neuronal transection and loss of fine dendritic processes, particularly during early development of neurons. However, the modified NanoSuit approach preserves neuronal morphology, enabling clear visualization of thin neurites and their interactions. Further, we successfully implemented correlative light and electron microscopy (CLEM) using this method, enabling the colocalization of cytoskeletal proteins such as actin and tubulin with the surface features observed by SEM. This combination of morphological preservation and molecular localization provides a more accurate and holistic understanding of neuronal structures, benefiting studies on neural development, synaptic connectivity, and related biomedical applications.