Background Recently, there has been much interest in the field of nanomedicine to improve prevention, diagnosis, and treatment. Combination therapy seems to be most effective when two different molecules that work by different mechanisms are combined at low dose, thereby decreasing the possibility of drug resistance and occurrence of unbearable side effects. Based on this consideration, the study was designed to investigate the combination effect of reduced graphene oxide-silver nanoparticles (rGO-AgNPs) and trichostatin A (TSA) in human ovarian cancer cells (SKOV3). Methods The rGO-AgNPs were synthesized using a biomolecule called lycopene, and the resultant product was characterized by various analytical techniques. The combination effect of rGO-Ag and TSA was investigated in SKOV3 cells using various cellular assays such as cell viability, cytotoxicity, and immunofluorescence analysis. Results AgNPs were uniformly distributed on the surface of graphene sheet with an average size between 10 and 50 nm. rGO-Ag and TSA were found to inhibit cell viability in a dose-dependent manner. The combination of rGO-Ag and TSA at low concentration showed a significant effect on cell viability, and increased cytotoxicity by increasing the level of malondialdehyde and decreasing the level of glutathione, and also causing mitochondrial dysfunction. Furthermore, the combination of rGO-Ag and TSA had a more pronounced effect on DNA fragmentation and double-strand breaks, and eventually induced apoptosis. Conclusion This study is the first to report that the combination of rGO-Ag and TSA can cause potential cytotoxicity and also induce significantly greater cell death compared to either rGO-Ag alone or TSA alone in SKOV3 cells by various mechanisms including reactive oxygen species generation, mitochondrial dysfunction, and DNA damage. Therefore, this combination chemotherapy could be possibly used in advanced cancers that are not suitable for radiation therapy or surgical treatment and facilitate overcoming tumor resistance and disease progression.

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Deep reinforcement learning (RL) has become one of the most popular topics in artificial intelligence research. It has been widely used in various fields, such as end-to-end control, robotic control, recommendation systems, and natural language dialogue systems. In this survey, we systematically categorize the deep RL algorithms and applications, and provide a detailed review over existing deep RL algorithms by dividing them into modelbased methods, model-free methods, and advanced RL methods. We thoroughly analyze the advances including exploration, inverse RL, and transfer RL. Finally, we outline the current representative applications, and analyze four open problems for future research.

Mammalian tooth development is regulated by paracrine signal molecules of several conserved family interactions between epithelium and mesenchyme. The expression patterns and regulative roles of FGF signaling have been extensively studied in the mouse odontogenesis; however, that is not well known in human tooth development. In order to unveil the molecular mechanisms that regulate human tooth morphogenesis, we examined the expression patterns of the critical molecules involved in FGF signaling pathway in the developing human tooth germ by in situ hybridization, immunohistochemistry, and real-time RT-PCR, including FGF ligands, receptors, and intracellular transducer. We found overlapping but distinct expression pattern of FGF ligands and receptors in the different stages and components. Expression of FGF4, FGF7, FGF8, and FGF9 persists widespread in human tooth mesenchyme, which is quite different to that of in mouse. FGFR1 may be the major receptor in regulate mechanisms of FGF signals in human tooth development. Real-time RT-PCR indeed confirmed the results of in situ hybridization. Results of K-Ras, p-ERK1/2, p-p38, p-JNK, and p-PDK1 expression reveal spatial and temporal patterns of FGF signaling during morphogenesis and organogenesis of human tooth germ. Activity of the FGF signaling transducer protein in human tooth germ was much higher than that of in mouse. Our results provided important FGF singling information in the developing process, pinpoint to the domains where the downstream target genes of FGF signaling can be sought, and enlightened our knowledge about the nature of FGF signaling in human tooth germ.

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