Microscopy Research and Technique最新文献

Plastic has been recognized as a major toxicological problem, but the recent detection of microplastics (MPs) in human fluids and tissues has raised global concern. MPs, mainly fibers and fragments, have been found in oceans, rivers, and lakes. Due to their small size (< 5 mm), aquatic organisms can accidentally ingest them and may ultimately reach humans through the food chain. This study assessed the gut response of Danio rerio exposed to different concentrations and shapes—microfibers (M.Fb.) and microfragments (M.Fg.)—polyethylene terephthalate (PET) MPs via feeding. Adult fish (n = 114) were exposed to 30 MPs for 24 h (acute toxicity) and to 1 or 6 MPs per feed per day for 15 and 30 days (chronic toxicity). The acute test revealed longer gut retention time for M.Fb. than M.Fg. Chronic exposure led to the detection of M.Fg. in gut sections. Histopathological analysis showed coalescence of villi, epithelial detachment, epithelial degeneration, muscle layer displacement, dysplasia, hypertrophy, hyperplasia, and necrosis, particularly at 6 MPs per feed. The histopathological alteration index (HAI) indicated greater damage with higher MP exposure, especially from M.Fb. Overall, these results suggest that in addition to concentration, the shape of the MPs also influences their impact on fish gut health, with M.Fb. exhibiting more severe effects of M.Fg.on the gut.

As a key representative of marine traditional Chinese medicine, Margaritifera Concha is commonly processed by calcination. However, significant differences in processing methods and quality standards have led to considerable variations in the quality of decoction pieces. Based on the theory of “quality evaluation through morphological identification,” this study investigates the microstructure and crystal phase composition of Margaritifera Concha and its calcined products, aiming to establish a new quality control approach distinct from traditional chemical index-based models. The microstructure of the “brick wall-cement-brick wall” pattern in Margaritifera Concha was examined using scanning electron microscopy and microscopic computed tomography, followed by 3D reconstruction and porosity calculations. The crystal phase composition was analyzed using x-ray diffraction, thermogravimetric analysis, and Fourier transform infrared spectroscopy. The results indicate that the calcination of Margaritifera Concha is closely associated with changes in its microstructural characteristics, and porosity can serve as a quantitative index for assessing the processing degree of decoction pieces.

Xenostrongylus variegatus (Nitidulidae: Nitidulinae) and Brassicogethes aeneus (Nitidulidae: Meligethinae) are two significant rapeseed pests in China. The former primarily feeds on leaves, while the latter exclusively targets flowers. Insect mouthparts are essential for feeding, with sensilla playing a critical role in food detection. This study compares the mouthpart sensilla of these two pests using scanning electron microscopy for the first time. Results revealed seven types (23 subtypes) of sensilla in male X. variegatus, seven types (21 subtypes) in female, and seven types (18 subtypes) in both male and female B. aeneus. Differences in the types, quantities, and distributions of sensilla were noted, with preliminary inferences made regarding their functions. These findings provide a foundation for further research into feeding behaviors, sensory systems, and integrated pest management strategies for rapeseed pests.

Dental air abrasion is a minimally invasive technique using abrasive particles to remove carious tooth structure. Alumina particles, commonly preferred due to their cutting efficiency, pose toxicity risks if inhaled. This study evaluated hydroxyapatite (HA) and an alumina + HA combination as alternatives to alumina for enamel cutting efficiency. Extracted human third molars with sound enamel (N = 30) were divided into three groups: (1) alumina 29 μm (control), (2) HA, and (3) alumina + HA. Morphological analysis of powders and cavity cutting performance were assessed using scanning electron microscopy (SEM). Alumina particles were coarse and angular, HA particles were rounded, and alumina + HA showed mixed morphology on SEM analysis. Cavity cutting results showed alumina produced the deepest cavities (mean: 2.5 mm), followed by alumina + HA (mean: 2.12 mm) and HA alone (mean: 0.75 mm). Statistically significant differences were detected between alumina and HA (p = 0.0003) and alumina + HA and HA (p = 0.008), but no significant differences between alumina and alumina + HA (p > 0.99) were observed. SEM analysis of the shape of the cavities revealed cylindrical shapes for alumina and alumina + HA groups and conical shapes for the HA group. The alumina + HA combination demonstrated effective enamel cutting efficiency while the presence of HA could be potentially useful for remineralization, presenting a safer alternative to pure alumina. Further in vivo studies are recommended to validate these findings.

Light (LM) and specular microscopies (SM) are standard techniques used by eye banks during corneal endothelial cell density (ECD) and morphology evaluation. This study aimed to develop a novel Hybrid method (HY) that integrates the benefits of both SM and LM while minimizing their drawbacks. A total of 283 endothelial images from LM and SM were analyzed from 31 corneas. For HY analysis, LM images were processed using SM-dedicated software to semi-automatically determine ECD, CV% (coefficient of variation), and HEX% (hexagonality). Agreements between LM, SM, and HY, as well as inter-operator bias, were assessed using the Bland–Altman analysis. Evaluability of corneas with LM, SM, and HY was recorded during 311 examinations on 70 corneas. HY agreed with SM in ECD determination, while LM differed from HY (bias: 134 cells/mm²) and SM (bias: 115 cells/mm²). HY showed agreement with SM in HEX% determination, while a bias of 3.4% was observed in CV%. Inter-operator variability analysis showed significant differences in LM evaluations (ECD, EC morphology score). For HY, no significant inter-operator bias was obtained in ECD and HEX%, whereas CV% displayed a significant bias (3.1%). Corneal evaluability was significantly higher in LM and HY (both 96.5%) than in SM (72.7%). HY enabled quantitative ECD and morphology investigation of corneal endothelia using LM-obtained images. HY, SM, and LM techniques statistically agreed in ECD and morphology examinations, or showed clinically acceptable bias. The HY method demonstrated lower inter-operator variability than LM and higher evaluability than SM.

Bioactive implant materials are those that can chemically and mechanically interface with live bone. Even metals, ceramics, and polymers that are normally bio-inert can be made to exhibit this quality by undergoing certain surface treatments. Immersion experiments in SBF, whose composition is comparable to that of human plasma, can be used for in vitro testing. As a result, an apatite coating may grow on the surface of the material, and the existence of this bone-like “biomimetic skin” is thought to predict bone-bonding capacity in vivo. Hydroxyapatite is a potential bioactive substance for bone tissue development and repair. However, its poor hardness limits its use in load-bearing applications. Recent research indicates that polylactic acid and polyhydroxyalkanoate have potential biocompatibility and can be used in bone implant applications. The current research aims to create biomimetic polylacticacid/polyhydroxyalkanoate/hydroxyapatite composite for bone tissue applications by integrating the biological recognition of natural polymers with the distinct interconnecting porosity and bio imitating features of bone, such as hydroxyapatite. The resultant PLA/PHA/10%HAP biopolymer composite was analyzed for biocompatibility by scanning electron microscopy (SEM), energy dispersive x-ray spectroscopy (EDX) and x-ray diffraction (XRD). The XRD analysis shows that the biopolymer composite's surface contains peaks indicative of an apatite phase. The development of an apatite layer is seen by SEM pictures. Ca/P ratio was calculated and found to be extremely near to 1.67, the value for original HAP, suggesting that EDX elemental analysis successfully confirmed the existence of calcium and phosphate components.

Leukemia remains a prevalent hematologic malignancy, and its morphological heterogeneity presents challenges for reliable identification under optical microscopy. To address this, we propose a frequency-domain guided object detection framework to assist leukemia diagnosis using high-resolution bone marrow microscopic images. Specifically, we leverage frequency-based image enhancement and refined feature integration to improve the detection and classification of leukemic cells. By combining spatial and frequency information, our approach captures both fine-grained details and broader semantic patterns critical for accurate diagnosis. We validated our method on clinical microscopic images, achieving high precision in distinguishing acute lymphocytic leukemia (ALL) and chronic lymphocytic leukemia (CLL), with average precision rates of 89.7% and 95.6%, respectively. Our findings demonstrate the value of integrating artificial intelligence with optical microscopy for enhanced diagnostic accuracy in leukemia classification.

Papillary thyroid carcinoma (PTC) is the most prevalent type of thyroid cancer, with a significant proportion of patients being susceptible to lymph node metastasis (LNM). The presence of LNM has been shown to accelerate tumor progression. Existing diagnostic approaches, such as ultrasonography and postoperative pathological analysis, exhibit limited sensitivity in detecting non-metastatic cases, thus undermining subsequent treatment planning. In this investigation, an innovative automated quantitative histological classification framework called the Automatic Thyroid Cancer Lymph Node Metastasis Classification Network (AutoThyroLNMNet) is introduced, which integrates Second-harmonic generation (SHG) imaging technology with deep learning to detect LNM in thyroid cancer. A combined model was constructed utilizing the Pyramid Vision Transformer v2 (PVTv2) as the backbone of the deep learning architecture and incorporating a multi-layer perceptron to fuse deep learning outputs, pathological information, and the two categories of collagen features. The models demonstrated a strong performance on training sets, with the highest efficacy achieved for the model that incorporated 3D texture features, achieving an area under the receiver operating characteristic (ROC) curve of 0.99. These results suggest that AutoThyroLNMNet is capable of automatically and quantitatively classifying lymph node metastasis in thyroid cancer, offering a novel and effective tool for the precise detection of LNM.

Medical Image plays a vital role in diagnosis, but noise in patient scans severely affects the accuracy and quality of images. Denoising methods are important to increase the clarity of these images, particularly in low-resource settings where current diagnostic roles are inaccessible. Pneumonia is a widespread disease that presents significant diagnostic challenges due to the high similarity between its various types and the lack of medical images for emerging variants. This study introduces a novel Diffusion with swin transformer-based Optimized Crow Search algorithm to increase the image's quality and reliability. This technique utilizes four datasets such as brain tumor MRI dataset, chest X-ray image, chest CT-scan image, and BUSI. The preprocessing steps involve conversion to grayscale, resizing, and normalization to improve image quality in medical image (MI) datasets. Gaussian noise is introduced to further enhance image quality. The method incorporates a diffusion process, swin transformer networks, and optimized crow search algorithm to improve the denoising of medical images. The diffusion process reduces noise by iteratively refining images while swin transformer captures complex image features that help differentiate between noise and essential diagnostic information. The crow search optimization algorithm fine-tunes the hyperparameters, which minimizes the fitness function for optimal denoising performance. The method is tested across four datasets, indicating its optimal effectiveness against other techniques. The proposed method achieves a peak signal-to-noise ratio of 38.47 dB, a structural similarity index measure of 98.14%, a mean squared error of 0.55, and a feature similarity index measure of 0.980, which outperforms existing techniques. These outcomes reflect that the proposed approach effectively enhances the quality of images, resulting in precise and dependable diagnoses.

Electrospun nanofibers offer sufficiently large pore size, good porosity, and interconnectivity for the integration of cells into the scaffold. Consequently, there has been a lot of interest in tissue engineering with electrospun nanomaterials. Numerous cellular functions can be supported by biocompatible conducting polymers. In this study, polyacrylonitrile (PAN)/polypyrrole (PPy) nanofibrous films were prepared by the electrospinning technique and examined as a scaffold for IHOEC ovarian cell attachment and proliferation. The rationale for embedding ovarian cells in a scaffold is particularly relevant to fields such as ovarian tissue engineering, infertility treatments, and postcancer tissue repair. This approach aims to enable cells to grow and form functional tissue in an environment similar to their natural microenvironment. Straight, smooth, and beadless PAN/PPy nanofibers with an average diameter of 216 ± 35 nm were obtained and analyzed by AFM, SEM, TEM, TGA, XRD, and WCA characterization methods. WCA measurements revealed that the nanofibers exhibited hydrophilic behavior, with WCA values of 14.93° ± 0.37 and 12.51° ± 0.50 being measured for the PAN and PAN/PPy nanofibers, respectively. PAN/PPy nanofibrous scaffolds were examined as a tissue engineering scaffold material for IHOEC ovarian cells, and the morphological properties and viability of cells grown on PAN/PPy nanofibers were observed. Results from the MTT test and SEM pictures demonstrated that IHOEC cells could adhere and proliferate on nanofibers. Consequently, PAN/PPy nanofibrous mats would be a potential candidate for an ovarian tissue scaffold.