X-ray excited optical luminescence from nanophosphors can be used to selectively generate light in tissue for imaging and stimulating light-responsive materials and cells. Herein, we synthesized X-ray scintillating NaGdF:Eu and Tb nanophosphors co-precipitate and hydrothermal methods, encapsulated with silica, functionalized with biotin, and characterized by X-ray excited optical luminescence spectroscopy and imaging. The nanophosphors synthesized by co-precipitate method were ∼90 and ∼106 nm in diameter, respectively, with hydrothermally synthesized particles showing the highest luminescence intensity. More importantly, we investigated the effect of thermal annealing/calcination on the X-ray excited luminescence spectra and intensity. At above 1000 °C, the luminescence intensity increased, but particles fused together. Coating with a 15 nm thick silica shell prevented particle fusion and enabled silane-based chemical functionalization, although luminescence decreased largely due to the increased mass of non-luminescent material. We observed an increase in luminesce intensity with temperature until at 400 °C. At above 600 °C, NaGdF:Eu@SiO converts to NaGdSiO:Eu, an X-ray scintillator brighter than annealed NPs at 400 °C and dimmer than NPs synthesized using the hydrothermal method. The particles generate light through tissue and can be selectively excited using a focused X-ray source for imaging and light generation applications. The particles also act as MRI contrast agents for multi-modal localization.
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http://dx.doi.org/10.1039/d1ra05451a | DOI Listing |
Sci Rep
January 2025
Department of Applied Mathematics, University of Waterloo, Waterloo, ON, N2L 3G1, Canada.
In the field of medical imaging, particularly MRI-based brain tumor classification, we propose an advanced convolutional neural network (CNN) leveraging the DenseNet-121 architecture, enhanced with dilated convolutional layers and Squeeze-and-Excitation (SE) networks' attention mechanisms. This novel approach aims to improve upon state-of-the-art methods of tumor identification. Our model, trained and evaluated on a comprehensive Kaggle brain tumor dataset, demonstrated superior performance over established convolution-based and transformer-based models: ResNet-101, VGG-19, original DenseNet-121, MobileNet-V2, ViT-L/16, and Swin-B across key metrics: F1-score, accuracy, precision, and recall.
View Article and Find Full Text PDFJ Chem Theory Comput
January 2025
Max-Planck-Institut für Kohlenforschung, Kaiser-Wilhelm-Platz 1, 45470 Mülheim an der Ruhr, Germany.
X-ray absorption spectroscopy (XAS) is a powerful method for exploring molecular electronic structure by exciting core electrons into higher unoccupied molecular orbitals. In this study, we present the first integration of the spin-unrestricted similarity-transformed equation-of-motion coupled cluster method (CVS-USTEOM-CCSD) for core-excited and core-ionized states into the ORCA quantum chemistry package. Using the core-valence separation (CVS) approach, we evaluate the accuracy of CVS-USTEOM-CCSD across 13 open-shell organic systems, covering over 20 core excitations with diverse spin multiplicities (doublet, triplet, and quartet).
View Article and Find Full Text PDFAdv Mater
January 2025
State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, 310027, China.
Traditional energy-integration X-ray imaging systems rely on total X-ray intensity for image contrast, ignoring energy-specific information. Recently developed multilayer stacked scintillators have enabled multispectral, large-area flat-panel X-ray imaging (FPXI), enhancing material discrimination capabilities. However, increased layering can lead to mutual excitation, which may affect the accurate discrimination of X-ray energy.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Data Science and Artificial Intelligence, Sunway University, 47500, Petaling Jaya, Selangor Darul Ehsan, Malaysia.
Precise segmentation of retinal vasculature is crucial for the early detection, diagnosis, and treatment of vision-threatening ailments. However, this task is challenging due to limited contextual information, variations in vessel thicknesses, the complexity of vessel structures, and the potential for confusion with lesions. In this paper, we introduce a novel approach, the MSMA Net model, which overcomes these challenges by replacing traditional convolution blocks and skip connections with an improved multi-scale squeeze and excitation block (MSSE Block) and Bottleneck residual paths (B-Res paths) with spatial attention blocks (SAB).
View Article and Find Full Text PDFACS Cent Sci
January 2025
Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States.
Inelastic photoelectron scattering (IPES) by gas molecules, a critical phenomenon observed in ambient pressure X-ray photoelectron spectroscopy (APXPS), complicates spectral interpretation due to kinetic energy loss in the primary spectrum and the appearance of additional features at higher binding energies. In this study, we systematically investigate IPES in various gas environments using APXPS, providing detailed insights into interactions between photoelectrons emitted from solid surfaces and surrounding gas molecules. Core-level XPS spectra of Au, Ag, Zn, and Cu metals were recorded over a wide kinetic energy range in the presence of CO, N, Ar, and H gases, demonstrating the universal nature of IPES across different systems.
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