Search

Osteosarcoma (OS) is a primary malignant bone tumor that occurs mainly in adolescents. Researchers are devoting to develop combination therapy methods in a multifunctional nanoplatform for the treatment of osteosarcoma. The results of previous research have shown that up-regulation of miR-520a-3p could induce anticancer effects in osteosarcoma. In order to improve the effect of gene therapy (GT), we attempted to carry miR-520a-3p in a multifunctional vector for comprehensive therapy. Fe2O3 is a type of magnetic resonance imaging (MRI) contrast that is widely used as a drug delivery agent. When coated with polydopamine (PDA), it can also be used as a photothermal therapy (PTT) agent (Fe2O3@ PDA). To deliver nanoagents targeted to a tumor site, folic acid (FA) conjugated with Fe2O3 @PDA was manufactured as FA-Fe2O3@PDA. FA was chosen as the target molecule to enhance utilization and reduce toxicity of nanoparticles. However, the therapeutic efficacy of FA-Fe2O3-PDA combined with miR-520a-3p has not yet been studied. In this study, we synthesized FA-Fe2O3@PDA-miRNA and investigated the potential of combining PDA regulated PTT and miR-520a-3p regulated GT to kill osteosarcoma cells. The results indicated that down-regulation of interleukin 6 receptor (IL6R) by miR-520a-3p and the photothermal ability of PDA could induce satisfactory anticancer effects in osteosarcoma, and the curative ratio was better than that used alone PTT or GT. Moreover, as a kind of T 2 magnetic contrast, miRNA-Fe2O3@PDA-FA can be used for MRI. These findings indicated that miRNA-Fe2O3@PDA-FA is an effective anti-tumor nanovector for PTT combined with GT. [ABSTRACT FROM AUTHOR]

Alcoholic liver disease is an important cause of death worldwide. Hepatocyte apoptosis is commonly observed in alcoholic liver disease. In this study, we investigated the effect of ginsenoside Rg1 (G‐Rg1), an organic component of ginseng, on the alcohol‐induced morphological and biophysical properties of hepatocytes. Human hepatocytes (HL‐7702) were treated in vitro with alcohol and G‐Rg1. The cell morphology was observed using scanning electron microscopy. Cell height, roughness, adhesion, and elastic modulus were detected using atomic force microscopy. We found that alcohol significantly induced hepatocyte apoptosis, whereas G‐Rg1 attenuated the alcohol‐induced hepatocyte damage. Scanning electron microscopy revealed that alcohol‐induced significant morphological changes in hepatocytes, including decreased cell contraction, roundness, and pseudopods, whereas G‐Rg1 inhibited these negative changes. Atomic force microscopy revealed that alcohol increased the cell height and decreased the adhesion and elastic modulus of hepatocytes. Following treatment with G‐Rg1, the cell height, adhesion, and elastic modulus of alcohol‐injured hepatocytes were all similar to those of normal cells. Thus, G‐Rg1 can attenuate the alcohol‐induced damage to hepatocytes by modulating the morphology and biomechanics of the cells. Research Highlights: In this study, the morphological characteristics of hepatocytes were observed using SEM.The changes in hepatocyte three‐dimensional images and biomechanical action caused by alcohol and G‐Rg1 were examined at the nanoscale using AFM under near‐physiological conditions.Alcohol‐induced hepatocytes showed abnormal morphology and biophysical properties. G‐Rg1 attenuated the alcohol‐induced damage to hepatocytes by modulating the morphology and biomechanics of the cells. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma is a high‐risk malignant tumor. Hepatoma cells are transformed from normal cells and have unique surface nanofeatures in addition to the characteristics of the original cells. In this paper, atomic force microscopy was used to extract the three‐dimensional morphology and mechanical information of HL‐7702 human hepatocytes and SMMC‐7721 and HepG2 hepatoma cells in culture, such as the elastic modulus and viscoelasticity. The characteristics of different cells were compared and analyzed. Finally, the cell morphology and mechanics information were used for training machine learning algorithms. With the trained model, the detection of cells was realized. The classification accuracy was as high as 94.54%, and the area under the receiver operating characteristic (ROC) curve (AUC) was 0.99. Thus, hepatocytes and hepatoma cells were accurately identified and assessed. We also compared the classification effects of other machine learning algorithms, such as support vector machine and logistic regression. Our method extracts cellular nanofeatures directly from the surface of cells of unknown type for cell classification. Compared with microscope image‐based analysis and other methods, this approach can avoid the misjudgment that may occur when different doctors have different levels of experience. Thus, the proposed method provides an objective basis for the early diagnosis of hepatocellular carcinoma. Research Highlights: The 3D appearance and mechanical characteristics of hepatocellular carcinoma cells are very similar to those of hepatocytes.Application of atomic force microscopy with machine learning algorithm.Collect the data set of nano‐characteristic parameters of the cell.The machine learning algorithms is trained by data set, and its classification effect is better than that of a single nano‐parameter. [ABSTRACT FROM AUTHOR]