Microscopy Images Research Articles

Effect of Er: YAG laser and different surface treatment methods on the push-out bond strength of glass fiber post to self adhesive resin cement

To compare the push-out bond strength of adhesive resin cement and glass fiber posts (GFP) at different root levels after exposure to Er: YAG laser irradiation compared to other conventional surface treatment procedures. A total of 24 mandibular premolars were decoronated, root canal treatment was done, post spaces were prepared, and roots were mounted in acrylic resin blocks. Fiber posts were divided into four groups (n = 6) according to surface treatment methods: (1) silane only (control group), (2) Er: YAG laser 1.5 W + silane, (3) 30% hydrogen peroxide + silane, (4) sandblasting with 50 μm aluminum oxide particles + silane. GFP were cemented using self-adhesive resin cement. Scanning electron microscope images with 500x magnification were taken for all groups. Push-out test was performed using a universal testing machine at different root levels. The difference between groups was statistically significant with laser group recording the highest mean ± SD value of push-out bond strength (5.668042 ± 1.16 MPa), followed by the H2O2 group, then the control group, meanwhile the lowest value was recorded with Sand-blasting group. There were no statistically significant differences between the Control group and Er: YAG group; Control group and sandblasted group. The difference between the radicular regions was not statistically significant, with the middle region recorded the highest push-out bond strength (4.746851 ± 0.73 MPa). GPF surface treatment using an Er: YAG laser is effective as it increases the retention to resin cement, while sandblasting decreases fiber post retention to resin cement. The hydrogen peroxide and the control groups give similar bond strength. The middle and apical regions of GFP have better retention to resin cement than the coronal one.

Inhibition of tumour necrosis factor alpha by Etanercept attenuates Shiga toxin-induced brain pathology

Infection with enterohemorrhagic E. coli (EHEC) causes severe changes in the brain leading to angiopathy, encephalopathy and microglial activation. In this study, we investigated the role of tumour necrosis factor alpha (TNF-α) for microglial activation and brain pathology using a preclinical mouse model of EHEC infection. LC–MS/MS proteomics of mice injected with a combination of Shiga toxin (Stx) and lipopolysaccharide (LPS) revealed extensive alterations of the brain proteome, in particular enrichment of pathways involved in complement activation and coagulation cascades. Inhibition of TNF-α by the drug Etanercept strongly mitigated these changes, particularly within the complement pathway, suggesting TNF-α-dependent vasodilation and endothelial injury. Analysis of microglial populations using a novel human-in-the-loop deep learning algorithm for the segmentation of microscopic imaging data indicated specific morphological changes, which were reduced to healthy condition after inhibition of TNF-α. Moreover, the Stx/LPS-mediated angiopathy was significantly attenuated by inhibition of TNF-α. Overall, our findings elucidate the critical role of TNF-α in EHEC-induced brain pathology and highlight a potential therapeutic target for mitigating neuroinflammation, microglial activation and injury associated with EHEC infection.Graphical

Mutations in the kinesin KIF12 promote MASH in humans and mice by disrupting lipogenic enzyme turnover.

As a common cause of liver cirrhosis, metabolic dysfunction-associated steatohepatitis (MASH) is regarded as a target of therapeutic intervention. However, a successful therapy has not yet been found, partly because the molecular pathogenesis is largely elusive. Here we show that KIF12 kinesin suppresses MASH development by accelerating the breakdown of two lipid biosynthesis enzymes, acetyl-CoA carboxylase 1 (ACC1) and pyruvate carboxylase (PC), in hepatocytes. We report three familial early-onset liver cirrhosis pedigrees with homozygous KIF12 mutations, accompanying MASH-like steatosis and cholestasis. The mouse genetic model carrying the corresponding Kif12 nonsense mutation faithfully reproduced the phenotypes as early as between 8 and 10 weeks of age. Furthermore, KIF12-deficient HepG2 cells exhibited significant steatosis, which was ameliorated by overexpressing a proline-rich domain (PRD) of KIF12. We found that KIF12-PRD promotes the degradation of ACC1 and PC, and this effect is likely to be through its direct interaction with these enzymes. Interestingly, KIF12 enhanced the ubiquitination of ACC1 by the E3 ligase COP1 and colocalized with these proteins as seen by super-resolution microscopy imaging. These data propose a role for KIF12 in suppressing MASH by accelerating turnover of lipogenic enzymes.

Safirinium Fluorescent “Click” Molecular Probes: Synthesis, CuAAC Reactions, and Microscopic Imaging

Safirinium Fluorescent “Click” Molecular Probes: Synthesis, CuAAC Reactions, and Microscopic Imaging

Experimental Study on Shear Thickening Polishing of ZnS Glass

Zinc sulfide (ZnS) is extensively utilized in various applications due to its exceptional optical transmittance across numerous spectral bands. To achieve ultra-high surface quality ZnS optical components, shear thickening polishing (STP) is employed to reduce roughness. A comparison between traditional fixed abrasive polishing (FAP) and STP for ZnS glass showed that FAP results in poor surface quality due to its low removal efficiency and uneven abrasive exposure, while STP provides better surface quality due to its flexible removal process, proving its feasibility and advancement. The Taguchi method was used to study the impact of three key polishing parameters on surface roughness (Ra) and the material removal rate (MRR), finding that polishing angle most influenced roughness and speed most influenced MRR. With optimal parameters, ZnS glass surface roughness was reduced from 110 ± 15 nm to 8.85 ± 0.5 nm, with an MRR of 32.5 nm/min. Scanning electron microscope (SEM) images further confirmed STP’s effectiveness in removing microdefects and smoothing the ZnS glass surface, offering a new method for the efficient, high-quality polishing of chalcogenide glasses without surface damage.

Highly tunning of dielectric and photocatalytic properties of crystalline ZnO semiconductor: functionality of Ba additives

Abstract In the present work, the concentration of Ba-additive played a significant role in advancing the dielectric properties and photo-removal activity of ZnO semiconductor for methylene blue dye. Ba doped ZnO semiconductor with different doping concentrations (Zn1-xBaxO, x = 0.003, 0.005, 0.007 and 0.009 wt.%) were grown by solid-state reaction route. The X-ray diffraction (XRD) data confirmed the formation of the wurtzite structure of ZnO along with the presence of BaO-based secondary phase (SP). The XRD peak intensity related to the SP was found to increase with the increase of Ba concentration. Microstructural analyses through scanning electron microscope (SEM) images and energy-dispersive X-ray analysis (EDS) showed that with the addition of Ba, a gradual increase in the grain size was observed. Furthermore, SP segregated at the grain boundary and showed an increasing trend with doping. The emergence of secondary phases with Ba concentration was confirmed with the help of supplementary spectroscopic characterizations including Fourier transform infrared spectroscopy (FTIR) and UV-Vis diffuse reflectance. The presence of BaO secondary phase has shown a benefit effect on the dielectric and photodegradation properties of ZnO material. The remarkable resistance reduction suggested that the higher Ba concentrations significantly enhance charge carrier mobility. For wastewater treatment uses, BZO9 photocatalyst exhibited a perfect degradation efficiency of 90.1% for methylene blue (MB) removal after 210 min of visible light illumination.

Insights into the Morphological Effects of 1D, 2D, and 3D CoV-Layered Double Hydroxides on Their Electrochemical Performance in Supercapacitors.

In this study, bimetallic cobalt-vanadium-based layered double hydroxide (CoV-LDH) systems were developed by varying the Co/V molar ratios (1:1 and 2:1) and hydrothermal temperatures (120 and 180 °C). Structural analysis by X-ray diffraction (XRD), Raman, and Fourier-transform infrared (FTIR) spectroscopy indicated the successful formation of CoV-LDH with a unique structure and lattice distortions, reflecting the influence of both the metal concentrations and temperature on the crystal and chemical structures of the developed bimetallic systems. Similarly, the field-emission scanning electron microscopy (FESEM) and high resolution transmission electron microscopy (HRTEM) images revealed a flaky 2D nanosheet-like structure for the bimetallic CoV-LDH with a 1:1 ratio prepared at 120 °C (CVL1-120), whereas one-dimensional (1D) and three-dimensional (3D) morphologies were observed for other bimetallic CoV-LDH systems prepared with a different molar ratio (2:1) and/or temperature (180 °C). Electrochemical analysis performed in a three-electrode setup demonstrated a specific capacitance of 314.4 F g-1 at 1 A g-1 current density for CVL1-120, which is ∼4.5 and 5.2 times higher than those of monometallic Co and V-LDH, respectively. In addition, CVL1-120 exhibited an excellent capacitance retention of ∼97% over 5000 charge-discharge cycles with 100% Coulombic efficiency at 10 A g-1. Furthermore, the developed asymmetric device delivered an energy density of 36.5 Wh kg-1 and a power density of 1208.2 W kg-1. This enhanced performance of CVL1-120 was attributed to its two-dimensional (2D) flaky structures, with rich intercalated ions serving as electroactive sites, facilitating enhanced charge storage efficiency and improved stability, making it suitable as an electrode material for sustainable supercapacitors.

Evaluation of Glazing and Polishing for Novel Chairside CAD/CAM Lithium Disilicate Containing Virgilite Crystals.

This comparative in vitro study evaluated surface treatment methods for chairside CAD/CAM lithium disilicate enriched with virgilite using atomic force microscopy (AFM) imaging. Specimens were fabricated from two lithium disilicate materials: the traditional material (IPS e.max CAD, Ivoclar Vivadent, Schaan, Liechtenstein) and a virgilite-containing material (CEREC Tessera, Dentsply Sirona, Charlotte, NC, USA). Surface roughness (Ra) [in micrometers (μm)] was quantitatively assessed with AFM. The results demonstrated that IPS e.max CAD with glazing exhibited the smoothest surface with the lowest Ra values (10.03 ± 5.03 μm). In contrast, CEREC Tessera exhibited the highest surface roughness when treated with glazing (51.98 ± 12.31 μm), while the zirconia polishing system provided a smoother surface (15.44 ± 9.69 μm).

Digital Cytometry: Extraction of Forward and Side Scattering Signals From Holotomography.

Flow cytometry is a cornerstone technique in medical and biological research, providing crucial information about cell size and granularity through forward scatter (FSC) and side scatter (SSC) signals. Despite its widespread use, the precise relationship between these scatter signals and corresponding microscopic images remains underexplored. Here, we investigate this intrinsic relationship by utilizing scattering theory and holotomography, a three-dimensional quantitative phase imaging (QPI) technique. We demonstrate the extraction of FSC and SSC signals from individual, unlabeled cells by analyzing their three-dimensional refractive index distributions obtained through holotomography. Additionally, we introduce a method for digital windowing of SSC signals to facilitate effective segmentation and morphology-based cell type classification. Our approach bridges the gap between flow cytometry and microscopic imaging, offering a new perspective on analyzing cellular characteristics with high accuracy and without the need for labeling.

Synthesis of FeSiAl/SrFe12O19 soft magnetic composite materials with low magnetic loss

AbstractFeSiAl/SrFe12O19 soft magnetic composite material was prepared by mechanically crushing FeSiAl powder and M‐type permanent magnet hexagonal ferrite powder according to a certain quality. Their structures, morphologies, and magnetic properties were studied using x‐ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), SQUID, and B−H analyzers. Compared to organic and other inorganic composite materials, SrFe12O19 has a higher thermal decomposition temperature. The x‐ray diffraction pattern indicates that SrFe12O19 phase was detected in the sample. Scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) images show that powdered SrFe12O19 is dispersed on the surfaces and gaps of particles of different sizes. The magnetic analysis results indicate that although SrFe12O19 increases the hysteresis loss of the material, its good insulation reduces eddy current loss. When the content of SrFe12O19 is 2 wt.‐%, the magnetic loss is the lowest. The lower magnetic loss and higher thermal decomposition temperature of this composite material make it have a wider range of application prospects.

Lyotropic Liquid Crystal Mediated Assembly of Donor Polymers Enhances Efficiency and Stability of Blade-Coated Organic Solar Cells.

Conjugated polymers can undergo complex, concentration-dependent self-assembly during solution processing, yet little is known about its impact on film morphology and device performance of organic solar cells. Herein, lyotropic liquid crystal (LLC) mediated assembly across multiple conjugated polymers is reported, which generally gives rise to improved device performance of blade-coated non-fullerene bulk heterojunction solar cells. Using D18 as a model system, the formation mechanism of LLC is unveiled employing solution X-ray scattering and microscopic imaging tools: D18 first aggregates into semicrystalline nanofibers, then assemble into achiral nematic LLC which goes through symmetry breaking to yield a chiral twist-bent LLC. The assembly pathway is driven by increasing solution concentration - a common driving force during evaporative assembly relevant to scalable manufacturing. This assembly pathway can be largely modulated by coating regimes to give 1) lyotropic liquid crystalline assembly in the evaporation regime and 2) random fiber aggregation pathway in the Landau-Levich regime. The chiral liquid crystalline assembly pathway resulted in films with crystallinity 2.63 times that of films from the random fiber aggregation pathway, significantly enhancing the T80 lifetime by 50-fold. The generality of LLC-mediated assembly and enhanced device performance is further validated using polythiophene and quinoxaline-based donor polymers.

Multispectral Interferometric Scattering Microscopy Imaging of Gold and Silver Nanoparticles

Multispectral Interferometric Scattering Microscopy Imaging of Gold and Silver Nanoparticles

Motion-tolerant 3D volumetric multimodality microscopy imaging of human skin with subcellular resolution and extended field-of-view

Motion-tolerant 3D volumetric multimodality microscopy imaging of human skin with subcellular resolution and extended field-of-view

Tailoring of Creep Regime Domain Wall Dynamics in Perpendicularly Magnetized Pd/Co/Pd Trilayers

AbstractUnderstanding magnetic domain wall (DW) dynamics is vital for improving the performance of heavy metal/ferromagnet based spintronic devices. Pd/Co/Pd multilayers hosting perpendicular magnetic anisotropy and interfacial Dzyaloshinskii‐Moriya interaction are prototypes for high density magnetic memory devices. This work presents the creep regime DW dynamics in Pd/Co/Pd trilayers with Ta buffer layer excited by symmetric field‐induced domain wall motion using Kerr microscopy. A systematic increment of DW velocity with increasing Co thickness is observed. SQUID‐VSM measurements reveal that the effective anisotropy constant decreases with the Co layer, leading to an increased DW width. Kerr microscopy images confirm that the DW is becoming rougher with magnetic layer thickness because of the dominance of magnetostatic energy over the DW energy. Hard X‐ray photoemission spectroscopy (HAXPES) reveals the presence of alloying at interfaces of Co/Pd. The asymmetry in magnetic circular dichroism HAXPES at the Pd 3d edge pictures the induced magnetic moment in Pd which is consistent with the larger saturation magnetization obtained from vibrating sample magnetometry. Extended X‐ray absorption fine structure performed in out‐of‐plane and in‐plane geometry shows the disordered nature of the Co local environment with the interdiffusion of Pd atoms into Co causing an asymmetry in the bonds.

OoCount: A Machine-Learning Based Approach to Mouse Ovarian Follicle Counting and Classification.

The number and distribution of follicles in each growth stage provides a reliable readout of ovarian health and function. Leveraging techniques for three-dimensional imaging of ovaries in toto has the potential to uncover total, accurate ovarian follicle counts. Due to the size and holistic nature of these images, counting oocytes is time consuming and difficult. The advent of machine-learning algorithms has allowed for the development of ultra-fast, automated methods to analyze microscopy images. In recent years, these pipelines have become more accessible to non-specialists. We used these tools to create OoCount, a high-throughput, open-source method for automatic oocyte segmentation and classification from fluorescent 3D microscopy images of whole mouse ovaries using a deep-learning convolutional neural network (CNN) based approach. We developed a fast tissue-clearing and imaging protocol to obtain 3D images of whole mount mouse ovaries. Fluorescently labeled oocytes from 3D images were manually annotated in Napari to develop a training dataset. This dataset was used to retrain StarDist using a CNN within DL4MicEverywhere to automatically label all oocytes in the ovary. In a second phase, we utilize Accelerated Pixel and Object Classification, a Napari plugin, to sort oocytes into growth stages. Here, we provide an end-to-end pipeline for producing high-quality 3D images of mouse ovaries and obtaining follicle counts and staging. We demonstrate how to customize OoCount to fit images produced in any lab. Using OoCount, we obtain accurate oocyte counts from each growth stage in the perinatal and adult ovary, improving our ability to study ovarian function and fertility.

Morphology and phylogeny reveal Gymnopus pseudoandrosaceus sp. nov. (Agaricales, Basidiomycota) from Southwest China

Gymnopus pseudoandrosaceus sp. nov. is described from Southwest China. It is characterized by a brown marasmioid pileus, a shining black stipe, and abundant rhizomorphs, a pileipellis in the form of a cutis with encrusted pigments and without broom cells, and cheilocystidia with apical projections. The phylogenetic analysis placed the new species within the Gymnopus sect. Androsacei clade with well-supported lineages across Impudicae, Levipedes, Gymnopus, Androsacei, and Paragymnopus. Strong bootstrap values affirm these relationships, with notable diversity in Gymnopus indicating potential adaptive radiation. The pileipellis lacking broom cells is a rather unique feature in this section. Detailed morphological descriptions, basidiomata photographs, microscopic structure images, and phylogenetic analysis results are provided.

DeiT and Image Deep Learning-Driven Correction of Particle Size Effect: A Novel Approach to Improving NIRS-XRF Coal Quality Analysis Accuracy

Coal, as a vital global energy resource, directly impacts the efficiency of power generation and environmental protection. Thus, rapid and accurate coal quality analysis is essential to promote its clean and efficient utilization. However, combined near-infrared spectroscopy and X-ray fluorescence (NIRS-XRF) spectroscopy often suffer from the particle size effect of coal samples, resulting in unstable and inaccurate analytical outcomes. This study introduces a novel correction method combining the Segment Anything Model (SAM) for precise particle segmentation and Data-Efficient Image Transformers (DeiTs) to analyze the relationship between particle size and ash measurement errors. Microscopic images of coal samples are processed with SAM to generate binary mask images reflecting particle size characteristics. These masks are analyzed using the DeiT model with transfer learning, building an effective correction model. Experiments show a 22% reduction in standard deviation (SD) and root mean square error (RMSE), significantly enhancing ash prediction accuracy and consistency. This approach integrates cutting-edge image processing and deep learning, effectively reducing submillimeter particle size effects, improving model adaptability, and enhancing measurement reliability. It also holds potential for broader applications in analyzing complex samples, advancing automation and efficiency in online analytical systems, and driving innovation across industries.

Biofilm destruction activity of α-tocopherol against Staphylococcus aureus, Proteus mirabilis and Pseudomonas aeruginosa.

Antibiotic resistance and the persistence of sessile cells within biofilms complicate the eradication of biofilm-related infections using conventional antibiotics. This highlights the necessity for alternate therapy methods. The objective of this study was to investigate the biofilm destruction activity of α-tocopherol against Staphylococcus aureus, Proteus mirabilis and Pseudomonas aeruginosa on polystyrene. α-Tocopherol showed significant biofilm destruction activity on the pre-formed biofilms of S. aureus (45-46%), Pr. mirabilis (42-54%) and Ps. aeruginosa (28%). Resazurin assay showed that α-tocopherol disrupted all bacteria biofilms without interfering with their cell viability. Scanning electron microscope images showed lower bacterial cell count and less compacted cell aggregates on polystyrene surfaces after treatment with alpha-tocopherol. This study demonstrated the biofilm destruction activity of alpha-tocopherol against S. aureus, Pr. mirabilis and Ps. aeruginosa. α-Tocopherol could potentially be used to decrease biofilm-associated infections of these bacteria.

Fractal Analysis of Volcanic Rock Image Based on Difference Box-Counting Dimension and Gray-Level Co-Occurrence Matrix: A Case Study in the Liaohe Basin, China

Volcanic rocks, as a widely distributed rock type on the earth, are mostly buried deep within basins, and their internal structures possess characteristics by irregularity and self-similarity. In the study of volcanic rocks, accurately identifying the lithology of volcanic rocks is significant for reservoir description and reservoir evaluation. The accuracy of lithology identification can improve the success rate of petroleum exploration and development as well as the safety of engineering construction. In this study, we took the electron microscope images of four types of volcanic rocks in the Liaohe Basin as the research objects and comprehensively used the differential box-counting dimension (DBC) and the gray-level co-occurrence matrix (GLCM) to identify the lithology of volcanic rocks. Obtain the images of volcanic rocks in the research area and conduct preprocessing so that the images can meet the requirements of calculations. Firstly, calculate the different box-counting dimension. Divide the grayscale image into boxes of different scales and determine the differential box-counting dimension based on the variation of grayscale values within each box. The differential box-counting dimension of basalt ranges from 1.7 to 1.75, that of trachyte ranges from 1.82 to 1.87, that of gabbro ranges from 1.76 to 1.79, and that of diabase ranges from 1.78 to 1.82. Then, the gray-level co-occurrence matrix is utilized to extract four image texture features of volcanic rock images, namely contrast, energy, entropy, and variance. The recognition of four types of volcanic rock images is achieved by combining the different box-counting dimension and the gray-level co-occurrence matrix. This method has been experimentally verified by volcanic rock image samples. It has a relatively high accuracy in identifying the lithology of volcanic rocks and can effectively distinguish four different types of volcanic rocks. Compared with single-feature recognition methods, this approach significantly improves recognition accuracy, offers reliable technical support and a data basis for volcanic rock-related geological analyses, and drives the further development of volcanic rock research.

Evaluation of safe exposure time for two-photon microscopy imaging of acrylic-painted mock-ups

Abstract Nonlinear optical microscopies are widely used in the biological and biomedical fields, as they are non-invasive techniques that permit the safe structural and morphological characterisation of cells and tissues. They are increasingly being used in the Cultural Heritage field because of their ability to overcome some limits of the well-established optical techniques. However, since nonlinear optical microscopies use pulsed laser sources with high peak power, their application in Cultural Heritage raises concerns due to artworks’ unique, priceless, and delicate nature. In this paper, we present a new method for evaluating the photo-induced damage when using a near-infrared femtosecond pulsed laser to perform two-photon excited fluorescence imaging of acrylic-painted mock-ups. In particular, we explore herein several irradiation conditions, varying the exposure time and excitation power, in order to provide useful experimental indications for safely imaging acrylic paints with two-photon microscopy.