Considerable progress has been made in synthesizing "intelligent", biodegradable hydrogels that undergo rapid changes in physicochemical properties once exposed to external stimuli. These advantageous properties of stimulus-triggered materials make them highly appealing to diverse biomedical applications. Of late, research on the incorporation of light-triggered nanoparticles (NPs) into polymeric hydrogel networks has gained momentum due to their ability to remotely tune hydrogel properties using facile, contact-free approaches, such as adjustment of wavelength and intensity of light source. These multi-functional NPs, in combination with tissue-mimicking hydrogels, are increasingly being used for on-demand drug release, preparing diagnostic kits, and fabricating smart scaffolds. Here, the authors discuss the atomic behavior of different NPs in the presence of light, and critically review the mechanisms by which NPs convert light stimuli into heat energy. Then, they explain how these NPs impact the mechanical properties and rheological behavior of NPs-impregnated hydrogels. Understanding the rheological behavior of nanocomposite hydrogels using different sophisticated strategies, including computer-assisted machine learning, is critical for designing the next generation of drug delivery systems. Next, they highlight the salient strategies that have been used to apply light-induced nanocomposites for diverse biomedical applications and provide an outlook for the further improvement of these NPs-driven light-responsive hydrogels.
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JMIR Res Protoc
January 2025
Data and Web Science Group, School of Business Informatics and Mathematics, University of Manneim, Mannheim, Germany.
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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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