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B7-H3 CAR-T cell therapy combined with irradiation is effective in targeting bulk and radiation-resistant chordoma cancer cells.
J Immunother Cancer
January 2025
Department of Orthopedic Surgery, Cedars-Sinai Medical Center, Los Angeles, California, USA
Background: Chordoma is a slow-growing, primary malignant bone tumor that arises from notochordal tissue in the midline of the axial skeleton. Surgical excision with negative margins is the mainstay of treatment, but high local recurrence rates are reported even with negative margins. High-dose radiation therapy (RT), such as with proton or carbon ions, has been used as an alternative to surgery, but late local failure remains a problem.
View Article and Find Full Text PDFNano-Metal-Organic Frameworks Isolated in Mesoporous Structures.
Adv Mater
January 2025
School of Chemistry and Chemical Engineering, Testing Center, Yangzhou University, Yangzhou, 225009, P. R. China.
As an alternative to bulk counterparts, metal-organic framework (MOF) nanoparticles isolated within conductive mesoporous carbon matrices are of increasing interest for electrochemical applications. Although promising, a "clean" carbon surface is generally associated with poor compatibility and weak interactions with metal/ligand precursors, which leads to the growth of MOFs with inhomogeneous particle sizes on outer pore walls. Here, a general methodology for in situ synthesis of eight nanoMOF composites within mesochannels with high dispersity and stability are reported.
View Article and Find Full Text PDFMolecular profiling of frontal and occipital subcortical white matter hyperintensities in Alzheimer's disease.
Front Neurol
January 2025
Department of Neurology, Massachusetts General Hospital, Charlestown, MA, United States.
White matter hyperintensities (WMHs) are commonly detected on T2-weighted magnetic resonance imaging (MRI) scans, occurring in both typical aging and Alzheimer's disease (AD). Despite their frequent appearance and their association with cognitive decline in AD, the molecular factors contributing to WMHs remain unclear. In this study, we investigated the transcriptomic profiles of two commonly affected brain regions with coincident AD pathology-frontal subcortical white matter (frontal-WM) and occipital subcortical white matter (occipital-WM)-and compared with age-matched cognitively intact controls.
View Article and Find Full Text PDFIntegrating the modified amphiphilic Eleocharis tuberosa starch to stabilize curcuminoid-enriched Pickering emulsions for enhanced bioavailability, thermal stability, and retention of the hydrophobic bioactive compound.
Carbohydr Polym
March 2025
College of Biological and Food Engineering, Anhui Polytechnic University, Wuhu 241000, Anhui-, China; Wuhu Green Food Industrial Research Institute Co., Ltd., Wuhu 241000, Anhui- China. Electronic address:
The study involves the modification of a non-conventional starch isolated from the under-utilized variety of Chinese water chestnut (CWC (Eleocharis tuberosa) and integrating it to fabricate stabilized and curcumin-enriched Pickering emulsions with enhanced bioavailability, thermal stability, and retention of encapsulated curcumin. A time-efficient, semi-dried esterification method was used to prepare modified amphiphilic starches using 3, 6, or 9 % (w/v) octenyl succinic anhydride (OSA) and characterized through degree of substitution (DS), contact angle, particle size, scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and in-vitro digestibility. Moreover, Pickering emulsions were formulated using CWCS-OSA at 3 %, 6 %, or 9 % concentrations to serve as a carrier for curcumin to improve its water solubility and storage stability.
View Article and Find Full Text PDFFilling-well: An effective technique to handle incomplete well-log data for lithology classification using machine learning algorithms.
MethodsX
June 2025
Department of Geophysical Engineering, Institut Teknologi Sepuluh Nopember, Indonesia.
Lithology classification is crucial for efficient and sustainable resource exploration in the oil and gas industry. Missing values in well-log data, such as Gamma Ray (GR), Neutron Porosity (NPHI), Bulk Density (RHOB), Deep Resistivity (RS), Delta Time Compressional (DTCO), Delta Time Shear (DTSM), and Resistivity Deep (RD), significantly affect machine learning classification accuracy. This study applied three algorithms, extreme gradient boosting (XGBoost), K-nearest neighbours (KNN), and the artificial neural network (ANN), to handle missing values in well-log datasets, particularly datasets with extreme missing data (30 %).
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