FOF1-ATP synthase molecular motor biosensor for miRNA detection of colon cancer

Gao, Ying; Zhang, Jie; Pan, Jiexia; Ying, Sanjun; Lou, Bang; Yang, Qingliang; Hong, Weiyong; Yang, Gensheng

doi:10.1016/j.lfs.2023.121527

Cited by 7 publications

(5 citation statements)

References 28 publications

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“…This was more obvious in the group of the CUR-CHR ( Figure 11 d), suggesting that the therapeutic effect of CUR-CHR with the presence of F O F 1 -ATPase motor-embedded CHR was better than the free CUR. This could be explained by the motility of the F O F 1 -ATPase motors driven by the proton gradient in the microenvironment of the tumors [ 19 ]. Compared with the previous in vivo study [ 23 ] on the tumor-bearing rat model with drug administered by injection, the intranasally administered drug delivery system proposed by the present study showed a similar or even better anti-tumor efficacy.…”

Section: Resultsmentioning

confidence: 99%

“…Micro/nanomotors (MNMs) [ 15 , 16 ] have the ability to convert energy into propulsion and movement [ 17 ], enabling them to be self-propelled vehicles [ 18 ]. Thanks to their active mobility and also the miniaturized body size, MNMs have displayed tremendous potential for biomedical applications including biosensing [ 19 ], diagnosis, minimally invasive surgery and targeted cargo delivery [ 20 ]. However, there are still many ongoing challenges and critical issues that need to be addressed.…”

Section: Introductionmentioning

confidence: 99%

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FOF1-ATPase Motor-Embedded Chromatophore as Drug Delivery System: Extraction, Cargo Loading Ability and Mucus Penetration Ability

Lou

Zheng

et al. 2023

Pharmaceutics

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Mucosal drug delivery permits direct and prompt drug absorption, which is capable of reducing undesirable decomposition that occurs before absorption. However, mucus clearance of those mucosal drug delivery systems strongly retards their actual application. Herein, we propose chromatophore nanoparticles embedded with FOF1-ATPase motors to promote mucus penetration. The FOF1-ATPase motor-embedded chromatophores were firstly extracted from Thermus thermophilus by using a gradient centrifugation method. Then, the model drug (curcumin) was loaded onto the chromatophores. The drug loading efficiency and entrapment efficiency were optimized by using different loading approaches. The activity, motility, stability and mucus permeation of the drug-loaded chromatophore nanoparticles were thoroughly investigated. Both the in vitro and in vivo studies revealed that the FOF1-ATPase motor-embedded chromatophore successfully enhanced mucus penetration glioma therapy. This study indicates that the FOF1-ATPase motor-embedded chromatophore is a promising alternative as a mucosal drug delivery system.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

FOF1-ATPase Motor-Embedded Chromatophore as Drug Delivery System: Extraction, Cargo Loading Ability and Mucus Penetration Ability

Lou

Zheng

et al. 2023

Pharmaceutics

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“…This fact is one of the main reasons for applying CNN in this research. Several studies have been conducted regarding colon cancer, including (Bhattacharya et al, 2023;Fahami et al, 2021;Gao et al, 2023;Gerwert et al, 2023;Kaya et al, 2022;Murugesan et al, 2023;Rajput & Subasi, 2023;Rathore et al, 2015;Talukder et al, 2022;Toğaçar, 2021). This research uses a dataset obtained from the Kaggle repository, consisting of 10,000 histopathology images, with 5000 images of Colon Adenocarcinoma (colon aca) and 5000 images of Benign Colon (colon n) (Lung and Colon Cancer Histopathological Images | Kaggle, n.d.).…”

Section: Introductionmentioning

confidence: 99%

Deep Learning for Histopathological Image Analysis: A Convolutional Neural Network Approach to Colon Cancer Classification

Agustiani,

Rianto

2024

telematika.

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Colon cancer is a type of cancer that attacks the last part of the human digestive tract. Factors such as an unhealthy diet, low fiber consumption, and high animal protein and fat intake can increase the risk of developing this disease. Diagnosis of colon cancer requires sophisticated diagnostic procedures such as CT scan, MRI, PET scan, ultrasound, or biopsy, which are often time-consuming and require particular expertise. This study aims to classify colon cancer based on histopathological images using a dataset of 10,000 images. This data is divided into 7,950 images for training, 2,000 for testing, and 50 for validation, aiming to achieve effective generalization. The Convolutional Neural Network (CNN) method was applied in this research with a relatively shallow architecture consisting of 4 convolution layers, 2 fully connected layers, and 1 output layer. Research results were evaluated by looking at the accuracy value of 99.55%, precision value of 99.49%, recall of 99.59%, prediction experiments on several images, and loss and accuracy graphs to detect signs of overfitting. However, this research has limitations in determining hyperparameters and layer depth, which was only tested from 1 to 5 convolution layers. Therefore, there are still opportunities for further development, such as applying unique feature extraction before the classification process

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“…19−21 The two strategies mentioned above involve additional transfection of metal ions or fuel chains, which may complicate the design and operation of DNA nanomachines and alter the cell microenvironment. The third is the use of intracellular endogenous substances (such as mRNA 22,23 and ATP 24,25 ) as a driving force. For example, Li et al 18 reported the use of intracellular mRNA as fuel chains to drive toehold strand displacement in the specifically designed DNA nanomachines for miRNA imaging.…”

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confidence: 99%

“…One is driven by DNAzyme using the metal ions as a cofactor, where the target analyst activates the DNAzyme and then repeatedly cuts the fluorescent dye-labeled substrate strands to amplify the signal. − The second is driven by strand displacement, where the target molecule acts as a catalyst to activate cyclic signal amplification in the presence of the fuel chain. − The two strategies mentioned above involve additional transfection of metal ions or fuel chains, which may complicate the design and operation of DNA nanomachines and alter the cell microenvironment. The third is the use of intracellular endogenous substances (such as mRNA , and ATP , ) as a driving force. For example, Li et al reported the use of intracellular mRNA as fuel chains to drive toehold strand displacement in the specifically designed DNA nanomachines for miRNA imaging.…”

mentioning

confidence: 99%

Endogenous Enzyme-Powered DNA Nanomotor Operating in Living Cells for microRNA Imaging

Li,

Sun,

Zhou

et al. 2023

Anal. Chem.

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Accurate and specific imaging of low-abundance microRNA (miRNA) in living cells is extremely important for disease diagnosis and monitoring of disease progression. DNA nanomotors have shown great potential for imaging molecules of interest in living cells. However, inappropriate driving forces and complex design and operation procedures have hindered their further application. Here, we proposed an endogenous enzyme-powered DNA nanomotor (EEPDN), which employs an endogenous APE1 enzyme as fuel to execute repetitive cycles of motion for miRNA imaging in living cells. The whole motor system is constructed based on gold nanoparticles without other auxiliary additives. Due to the high efficiency of APE1, this EEPDN system has achieved highly sensitive miRNA imaging in living cells within 1.5 h. This strategy was also successfully used to differentiate the expression of specific miRNA between tumor cells and normal cells, demonstrating a high tumor cell selectivity. This strategy can promote the development of novel nanomotors and is expected to be a perfect intracellular molecular imaging tool for biological and medical applications.

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FOF1-ATP synthase molecular motor biosensor for miRNA detection of colon cancer

Cited by 7 publications

References 28 publications

FOF1-ATPase Motor-Embedded Chromatophore as Drug Delivery System: Extraction, Cargo Loading Ability and Mucus Penetration Ability

FOF1-ATPase Motor-Embedded Chromatophore as Drug Delivery System: Extraction, Cargo Loading Ability and Mucus Penetration Ability

Deep Learning for Histopathological Image Analysis: A Convolutional Neural Network Approach to Colon Cancer Classification

Endogenous Enzyme-Powered DNA Nanomotor Operating in Living Cells for microRNA Imaging

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