Microscopy Research and Technique最新文献

In the rapidly advancing field of histopathological image analysis, accurate segmentation of critical features is crucial for medical diagnostics, as it enables pathologists to make precise decisions. The proposed One Former-based Mean Teacher Model with Federated Learning (OF-MTMFL) system combines cutting-edge semi-supervised learning and federated learning techniques to tackle issues such as limited annotated data and class imbalance. The framework utilizes a mean teacher architecture, where the student model, guided by a focal loss function, prioritizes high-confidence regions in unlabeled data, while the teacher model ensures consistency through Exponential Moving Average (EMA) updates. To further enhance segmentation accuracy, multi-scale attention modules are employed for robust feature extraction. Additionally, the system incorporates a Federated Learning mechanism that allows multiple institutions to collaborate without sharing raw data, including datasets from the Cancer Genome Atlas (TCGA). The results from the analysis of the TCGA dataset indicate that the proposed OF-MTMFL model achieved mean concordance index (c-index) scores of 0.700 ± 0.030 for Bladder Urothelial Carcinoma (BLCA), 0.720 ± 0.040 for Breast Invasive Carcinoma (BRCA), 0.860 ± 0.025 for Glioblastoma & Lower Grade Glioma (GBMLGG), 0.690 ± 0.035 for Lung Adenocarcinoma (LUAD), and 0.740 ± 0.045 for Uterine Corpus Endometrial Carcinoma (UCEC). The overall performance score of the OF-MTMFL model across these cancer types is 0.740, demonstrating particularly strong results in GBMLGG while maintaining competitive scores in the other cancer types. The standard deviations reported reflect the variability of the model's performance across different samples within each category.

Senna martiana (Benth.) H.S. Irwin & Barneby is endemic to Brazil's dryland Caatinga domain. The species is known as “canafistula” in folk medicine, and its leaves are used as a laxative. Anatomical and histochemical studies of the species' vegetative organs (roots, stems, and leaves) were conducted to identify features that would support its taxonomic classification, as well as provide quality control for its ethnomedicinal use. Dried fragments from both leaflet surfaces were examined using scanning electron microscopy, and paradermal and transverse sections were used in histochemical tests to confirm the presence of lipids, starch, alkaloids, and nonstructural phenolic compounds. Senna martiana exhibits a striate cuticle on both leaflet surfaces, with straight to curved anticlinal cell walls on the adaxial face and sinuous walls on the abaxial face. The leaflets are amphistomatic, with a variety of stomatal types (paracytic, anisocytic, and anomotetracytic). The midrib is plane-convex with a collateral vascular system; the petiole is elliptic with 6–8 vascular bundles; the leaf rachis is ovate with 4–5 vascular bundles. Stems have a siphonostelic ectophloic vascular system. Idioblasts containing crystal sand, prismatic crystals, druses, and starch grains were observed in all vegetative organs. The contour and number of vascular bundles in the petiole and rachis, along with the sclerenchyma bundles enclosing the vascular system or roots, were distinctive features for Senna martiana. These characters constitute an important support for species identification, differentiation, and quality control of its ethnomedicinal drugs.

This study represents the first comprehensive effort to document the pollen taxonomy of plant species in the Hindukush-Karakoram-Himalaya region of northern Pakistan. The clarification of the leaf micromorphology of the selected herbaceous plants reveals characteristics like the stomata types, trichome types, and epidermal cell size and shape. The leaf micromorphology of 50 herbaceous plants revealed foliar anatomical traits, such as changes in epidermal cells, trichome morphology, and stomatal type. Stachys emodi has the longest epidermal cell length, measuring 69.54um at the adaxial and 66.65um at the abaxial surface. The largest guard cell length was recorded as 36.45 μm in Erigeron bonariensis , while the stomatal width measured 36.15 μm on the abaxial surface and 34.55 μm on the adaxial surface among the studied Asteraceous taxa. In anatomical features, diacytic, actinocytic, anomocytic, anisocytic, and paracytic stomata were studied. Anticlinal wall patterns were found to be undulating, straight, and sinuate. The epidermal cell shape was found to be polygonal, pentagonal, tetragonal, and irregular. The micromorphological epidermal anatomical traits have been recognized to serve as a foundation for the correct identification of herbaceous flora in the context of systematic relevance.

The green synthesis of nanoparticles using plant extracts has garnered significant attention as a reliable and sustainable method for producing functional nanomaterials. Among these, zinc oxide (ZnO) nanoparticles are extensively studied for their potential biological applications. In this study, ZnO nanoparticles were synthesized through a green synthesis approach using an aqueous extract of Musa acuminata leaves and zinc acetate as precursors. The resulting nanoparticles were characterized using ultraviolet–visible spectroscopy (UV–Vis), Fourier transform infrared spectroscopy (FTIR), x-ray diffraction analysis (XRD), energy-dispersive x-ray analysis (EDX), and scanning electron microscopy (SEM). The UV–Vis spectra revealed characteristic absorption peaks around 350 nm, attributed to the nanoparticles' large excitation binding energy at room temperature. FTIR analyses confirmed the formation of zinc oxide chemical bonds, while XRD results indicated a hexagonal wurtzite crystal structure. SEM analysis showed that the nanoparticles had a nearly cuboid shape, and EDX analysis confirmed their high purity. The minimum inhibitory concentrations (MIC) of the synthesized ZnO nanoparticles were evaluated against Staphylococcus aureus and Escherichia coli cultures. Cotton wound bandages impregnated with ZnO nanoparticles at concentrations near the calculated MIC demonstrated significant antibacterial activity in vitro. These antimicrobial bandages show potential for use in treating and protecting infection-prone wounds, such as diabetic or burn-related injuries.

Uterine cancer also referred to as endometrial cancer, which significantly impacts the female reproductive organs. The early diagnosis increases the survival rates and also prevents the progression of endometrial cancer thereby, the novel Transfer Learning based Convolution Neural Network with Adam Gold Rush Optimization (TL-CNN_AdGRO) is proposed to classify endometrial cancer using histopathological images. The histopathological image is fed to the preprocessing phase, which uses an Adaptive Weighted Mean Filter (AWMF). Next, the segmentation of endometrial cancer is utilized by the Directional Connectivity Network (DConn-Net). Following segmentation, feature mining is carried out, which includes Local Boundary Summation Pattern (LBSP) and Local Gaber Binary Pattern Histogram Sequence Features (LGBPHS). Finally, the endometrial cancer classification is achieved using TL-CNN by employing hyperparameters from the Xception model. Here TL-CNN is trained by AdGRO algorithm, which is the combination of Adam Optimizer and Gold Rush Optimization. Compared to existing models, the proposed model achieves superior performance with an accuracy of 91.876%, a True Positive Rate (TPR) of 93.987%, and a True Negative Rate (TNR) of 89.876% for K-sample 8. The results confirm the effectiveness of TL-CNN_AdGRO, also it demonstrates strong performance, ensures robustness, improves the early detection of endometrial cancer, and making it a promising approach for histopathological image analysis.

To assess the efficiency of Er; Cr: YSGG laser (ECL), Er: YAG laser (EYL), and the Ti: sapphire femtosecond laser (TsFL) in terms of color change (ΔE) measured by a spectrophotometer, surface topography observed through SEM, surface roughness (Ra), and bond strength of Lithium disilicate glass–ceramic (LDC) to resin cement. A total of 84 LDC disks were manufactured and assigned randomly into four groups. Group 1-HFA treated, Group 2 treated with TsFL, Group 3 with EYL, and Group 4 with ECL. Each disk was coated with a silane coupling agent. Surface profiling of the LDC disc was evaluated via SEM and Ra was measured using a profilometer. The ΔE values were determined using the CIE L*a*b* system. Adhesive luting cement was applied to 10 samples from each group, followed by thermocycling to simulate aging. Shear bond strength (SBS) was assessed, and failure modes were inspected following SBS. ANOVA and Tukey's post hoc test were used for the comparison of means and SD among groups. The highest ΔE was observed in the control HFA (4.23 ± 1.02) treated group. Whereas, Group 2 TsFL (2.22 ± 1.11) pretreated samples displayed the lowest ΔE. Ra and SBS analysis unveiled that the maximum score of Ra (1155.01 ± 1.43 μm) and SBS (10.28 ± 0.17 MPa) was observed in Group 2 TsFL. Group 4 (ECL) conditioned discs showed the lowest Ra (1015.41 ± 1.31 μm) and bond integrity (8.15 ± 0.16 MPa). The TsFL serves as an effective alternative to traditional surface preparation methods as it enhances the mechanical properties of LDC (SBS and Ra) with no susceptible change in ΔE.

In this work, five different molar concentrations of Bi₂MoO₆ are prepared using the hydrothermal method. SEM, XRD, and FTIR are used to find out the morphology of the synthesized materials as ratio 1 (1:1), 2 (0.8:1.2), 3 (1.2:0.8), 4 (0.6:1.4), and 5 (1.4:0.6). The newly formed nanomaterial is spherical to cubic in shape as per the SEM results, with some agglomerates. The water splitting and antibacterial activity of the electrocatalyst are carried out without any irradiation of light, which is the novelty of this research work. According to EIS (parameter of water splitting), the change transfer (R_ct) value for ratio 3 (1.2:0.8) is 5 Ω and the R_ct value for ratio 5 (1.4:0.6) is 8.48 Ω. The R_s value for ratio 1 (1:1) was very low, R_s = 5.77 Ω, compared to the R_s value for ratio 2 (0.8:1.2), R_s = 6.75 Ω. For instance, activity for ratio 1 (1:1) showed less overpotential for HER and OER, which led to more water splitting and a lower R_ct number. For a better understanding, all the electrochemical factors and the time sequence of the different Bi₂MoO₆ ratios should be looked at: 1:1 ratio > 0.8:1.2 ratio > 1.2:0.8 ratio > 0.6:1.4 ratio > 1.4:0.6 ratio. The experimental results suggest that a 1:1 ratio between Bi and Mo exhibits higher electrochemical as well as antibacterial activity results.