Ceria-Based Nanozymes in Point-of-Care Diagnosis: An Emerging Futuristic Approach for Biosensing

Wang, Ruixue; Du, Yuanyuan; Fu, Ying; Guo, Yingxin; Gao, Xing; Guo, Xingqi; Wei, Jingjing; Yang, Yanzhao

doi:10.1021/acssensors.3c01692

Cited by 13 publications

(4 citation statements)

References 185 publications

(268 reference statements)

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“…Due to their unique reaction characteristics, SANs provide great opportunities to improve medical diagnostic and treatment tools, such as biosensors and agents for imaging . The exact nature of SANs at the atomic level boosts sensitivity and selectivity when identifying biomolecules . Thus, SANs play an essential role in diagnostic sessions and are also very promising for medical devices.…”

Section: Opportunitiesmentioning

confidence: 99%

Unleashing the Potential of Single-Atom Nanozymes: Catalysts for the Future

Hamed,

Fung,

2024

ACS Sens.

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Single-atom nanozymes (SANs) have become a breakthrough in atomically precise catalysis, which relies on the catalytic active site formed by the single-atom itself. From this angle, SANs and their advantages compared to natural enzymes as well as spaces for their application are emphasized. The SANs have outstanding control over their catalytic activities; this is compared with bulk materials and natural enzymes. The structure of the SANs has very promising potential for the next generation of biosensing and biomedical devices and environmental remediation. Although their capabilities are high, difficulties still arise. The specificity, scalability, biosafety, and catalysis mechanisms raise additional issues that require further research. We build up a vision of the perspectives of the better implementation of SANs, which are designed for diagnostic purposes, improving industrial technologies, and creating new sustainable technologies in the food processing industry. AI and machine learning systems may clarify the structure−performance relationship of SANs for improved material and process selectivity. The future of SANs is very promising, and by addressing these challenges and leveraging advancements in artificial intelligence and materials science, SANs have the potential to become powerful tools for a sustainable future.

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Section: Opportunitiesmentioning

confidence: 99%

Unleashing the Potential of Single-Atom Nanozymes: Catalysts for the Future

Hamed,

Fung,

2024

ACS Sens.

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“…Since the discovery of Fe 3 O 4 nanoparticles’ peroxidase-like catalytic activity in 2007, numerous nanomaterials have been reported to mimic natural enzyme-like activities, collectively termed nanozymes. − Due to their high stability and environmental tolerance, nanozymes have been widely applied in various fields such as biosensing, , antibacterial, , antitumors, , and anti-infection. , To enhance catalytic activities of nanozymes for broadening their applications, researchers have exerted significant efforts in regulating the metal active center, , nonmetal doping, , morphologies, , surface modifications, buffer pH, temperature, and substrates . However, all experimental trials have been based on extensive literature review and individual cognitive experience, drawbacks of which include repetitive trial and error, time consumption, and high labor intensity. , Therefore, establishing a model for preliminary prediction of types and activities of nanozymes is of great importance.…”

Section: Introductionmentioning

confidence: 99%

ChatGPT Combining Machine Learning for the Prediction of Nanozyme Catalytic Types and Activities

Sun,

Hu,

Yang

et al. 2024

J. Chem. Inf. Model.

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The design of nanozymes with superior catalytic activities is a prerequisite for broadening their biomedical applications. Previous studies have exerted significant effort in theoretical calculation and experimental trials for enhancing the catalytic activity of nanozyme. Machine learning (ML) provides a forward-looking aid in predicting nanozyme catalytic activity. However, this requires a significant amount of human effort for data collection. In addition, the prediction accuracy urgently needs to be improved. Herein, we demonstrate that ChatGPT can collaborate with humans to efficiently collect data. We establish four qualitative models (random forest (RF), decision tree (DT), adaboost random forest (adaboost-RF), and adaboost decision tree (adaboost-DT)) for predicting nanozyme catalytic types, such as peroxidase, oxidase, catalase, superoxide dismutase, and glutathione peroxidase. Furthermore, we use five quantitative models (random forest (RF), decision tree (DT), Support Vector Regression (SVR), gradient boosting regression (GBR), and fully connected deep neuron network (DNN)) to predict nanozyme catalytic activities. We find that GBR model demonstrates superior prediction performance for nanozyme catalytic activities (R 2 = 0.6476 for Km and R 2 = 0.95 for Kcat). Moreover, an open-access web resource, AI-ZYMES, with a ChatGPT-based nanozyme copilot is developed for predicting nanozyme catalytic types and activities and guiding the synthesis of nanozyme. The accuracy of the nanozyme copilot's responses reaches more than 90% through the retrieval augmented generation. This study provides a new potential application for ChatGPT in the field of nanozymes.

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“…Cerium-based nanomaterials, such as cerium dioxide, , cerium metal–organic frameworks, , and cerium single-atom, have attracted much attention as nanozymes for biomedical applications because of their low cost, chemical stability, biocompatibility, multiple enzyme-like catalytic activities, and reactive oxygen species (ROS) generation and scavenging capacity. − Cerium oxysulfate clusters (Ce-clusters), as a novel oxides of cerium, have been predominantly investigated owing to their special doughnut-like configuration, variable valence states (Ce IV and Ce III ), and abundant Ce active sites. − Although Ce-clusters display potential properties for catalysis, their high crystallization and rapid assembly ability make them easy to form bulky rods, hindering their applications in the field of nanozymes.…”

Section: Introductionmentioning

confidence: 99%

Bringing Cerium Oxysulfate Clusters into Nanozymes by Saturated Fatty Acid Regulation for Oxidase-like Activity

Xue,

Li,

Jia

et al. 2024

ACS Appl. Nano Mater.

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Nanozymes have demonstrated superior properties compared to natural enzymes and traditional artificial enzymes in a variety of fields. Although significant progress has been achieved, it remains challenging to develop nanozymes with an adequate catalytic activity. Herein, we, for the first time, bring cerium oxysulfate cluster (Ce-clusters) materials into nanozyme research by a saturated fatty acid regulation strategy due to their potential catalytic activity. It is found that the saturated fatty acids can control the growth, assembly, and size of Ce-clusters in the coprecipitation process, which can enhance the oxidase-like activity of Ce-clusters. With the increase of the alkyl chain length, the catalytic activity gradually decreases because of the strengthened intermolecular interactions between fatty acids and clusters. Notably, the Ce-clusters synthesized with lauric acid present the highest oxidase-like activity among these Ce-clusters. The catalytic activity of nanozyme follows typical Michaelis−Menten kinetics, and the • O 2 − and h + are the main reactive species produced during the catalytic process. Benefiting from the excellent oxidase-like activity, the resultant nanozyme is successfully applied for reductive molecule colorimetric sensing applications. This study not only introduces Ce-clusters into nanozyme research and enriches the oxidase-mimicking nanozyme family but also provides an extremely simple strategy to enhance the catalytic activity of nanozymes, holding great promise in a wide variety of nanozyme applications.

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Ceria-Based Nanozymes in Point-of-Care Diagnosis: An Emerging Futuristic Approach for Biosensing

Cited by 13 publications

References 185 publications

Unleashing the Potential of Single-Atom Nanozymes: Catalysts for the Future

Unleashing the Potential of Single-Atom Nanozymes: Catalysts for the Future

ChatGPT Combining Machine Learning for the Prediction of Nanozyme Catalytic Types and Activities

Bringing Cerium Oxysulfate Clusters into Nanozymes by Saturated Fatty Acid Regulation for Oxidase-like Activity

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