Cerium oxide nanoparticles (Nanoceria) have shown promise as catalytic antioxidants in the test tube, cell culture models and animal models of disease. However given the reactivity that is well established at the surface of these nanoparticles, the biological utilization of Nanoceria as a therapeutic still poses many challenges. Moreover the form that these particles take in a biological environment, such as the changes that can occur due to a protein corona, are not well established. This review aims to summarize the existing literature on biological use of Nanoceria, and to raise questions about what further study is needed to apply this interesting catalytic material to biomedical applications. These questions include: 1) How does preparation, exposure dose, route and experimental model influence the reported effects of Nanoceria in animal studies? 2) What are the considerations to develop Nanoceria as a therapeutic agent in regards to these parameters? 3) What biological targets of reactive oxygen species (ROS) and reactive nitrogen species (RNS) are relevant to this targeting, and how do these properties also influence the safety of these nanomaterials?
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http://dx.doi.org/10.1039/C4EN00138A | DOI Listing |
JMIR Res Protoc
January 2025
Data and Web Science Group, School of Business Informatics and Mathematics, University of Manneim, Mannheim, Germany.
Background: The rapid evolution of large language models (LLMs), such as Bidirectional Encoder Representations from Transformers (BERT; Google) and GPT (OpenAI), has introduced significant advancements in natural language processing. These models are increasingly integrated into various applications, including mental health support. However, the credibility of LLMs in providing reliable and explainable mental health information and support remains underexplored.
View Article and Find Full Text PDFNano Lett
January 2025
Institute of Electronics, National Yang Ming Chiao Tung University, Hsinchu, 30010, Taiwan.
Deep-ultraviolet (DUV) light is essential for applications including fabrication, molecular research, and biomedical imaging. Compact metalenses have the potential to drive further innovation in these fields, provided they utilize a material platform that is cost-effective, durable, and scalable. In this work, we present aluminum nitride (AlN) metalenses as an efficient solution for DUV applications.
View Article and Find Full Text PDFPLoS One
January 2025
European IPF/ILD Registry and Biobank (eurIPFreg/bank, eurILDreg/bank), Giessen, Germany.
Background And Aims: Predicting progression and prognosis in Interstitial Lung Diseases (ILD), especially Idiopathic Pulmonary Fibrosis (IPF) and Progressive Pulmonary Fibrosis (PPF), remains a challenge. Integrating patient-centered measurements is essential for earlier and safer detection of disease progression. Home monitoring through e-health technologies, such as spirometry and oximetry connected to smartphone applications, holds promise for early detection of ILD progression or acute exacerbations, enabling timely therapeutic interventions.
View Article and Find Full Text PDFChem Commun (Camb)
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Marshall Laboratory of Biomedical Engineering, International Cancer Center, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Laboratory of Evolutionary Theranostics (LET), School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen 518055, China.
The introduction of fluorescence imaging (FLI) in near-infrared II sub-channels (NIR-IIb, 1500-1700 nm) has revolutionized the ability to explore complex patho-physiological settings . Despite the transformative potentials, the development of organic NIR IIb dyes encounters considerable difficulties, and only a limited number of such fluorophores have been developed so far. This review systematically introduces design strategies of organic NIR-IIb fluorophores classified by molecular scaffolds, mainly including cyanine dyes and D-A-D small molecule dyes.
View Article and Find Full Text PDFBr J Radiol
January 2025
2nd Department of Radiology, University General Hospital "ATTIKON", Medical School, National and Kapodistrian University of Athens, Greece.
In a rapidly evolving healthcare environment, artificial intelligence (AI) is transforming diagnostic techniques and personalised medicine. This is also seen in osseous biopsies. AI applications in radiomics, histopathology, predictive modelling, biopsy navigation, and interdisciplinary communication are reshaping how bone biopsies are conducted and interpreted.
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