DNA cages are ideally suited to make nanostructures which serve as containers for drug delivery. Using fewer strands to assemble DNA cages is of importance to the design of DNA molecules with multiple component strands. In this study, we propose a rational assembling procedure to design and analyze DNA bipyramids with minimum strands. The results show that the odd-half twist has a major impact on assembling strands required to construct DNA cages and this method could offer a search of DNA bipyramids with minimum component strands faster. This research provides new insights into design and synthesis for DNA bipyramid-like cages from mathematical perspective.
Additional file 2: Figure S1. Relative expression levels of E2F1 and EIF4A3 were determined by qRT-PCR. (a) Relative expression of E2F1 expression were evaluated in TNBC cells transfected with E2F1 overexpression plasmids or siRNA. (b) The relative expression of EIF4A3 was detected in TNBC cells transfected with EIF4A3 overexpression or knockdown plasmids. The data are presented as the mean ± SD, **P
miRNAs have emerged as promising markers for tumors. However, the underlying mechanism of specific miRNAs in bladder cancer (BC) remains largely unknown. Here, a comprehensive miRNA/mRNA expression profile was executed by microarray assay for four pairs of bladder carcinoma and para-carcinoma tissues from patients with grade 2 (G2) T2. A total of 99 miRNAs and 4416 mRNAs were discovered to be significantly differentially expressed in BC tissues compared with controls. Five microRNAs and two mRNAs were validated by qRT-PCR in 30 pairs of samples, including G1-G3/T1-T4. Subsequently, we constructed a network with the five miRNAs-target mRNAs; gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were utilized to recognize the functions and associated pathways. Moreover, we further found that miR-130b-3p was significantly up-regulated and negatively correlated with phosphatase and tensin homolog (PTEN) expression in bladder cancer tissues. Next, we demonstrated that miR-130b-3p might target PTEN through bioinformatics and dual-luciferase reporter assay. Finally, we showed that miR-130b-3p could down-regulate PTEN expression, which promoted proliferation, migration, invasion and rearranged cytoskeleton through the activation of the PI3K and integrin β1 signaling pathway in bladder cancer cells. Inversely, miR-130b-3p inhibitors induced apoptosis. Taken together, this research investigated, for the first time, miR-130b-3p by an incorporated analysis of microRNA/mRNA expressions of a genome-wide screen in BC. Our findings suggest that the miR-130b-3p/PTEN/integrin β1 axis could play a critical role in the progression and development of BC and that miR-130b-3p might be a valuable clinical marker and therapeutical target for BC patients.
Angiogenesis is the process by which new blood vessels form and is required for tumour growth and metastasis. It helps in supplying oxygen and nutrients to tumour cells and plays a crucial role in the local progression and distant metastasis of, and development of treatment resistance in, breast cancer. Tumour angiogenesis is currently regarded as a critical therapeutic target; however, anti‐angiogenic therapy for breast cancer fails to produce satisfactory results, owing to issues such as inconsistent efficacy and significant adverse reactions. As a result, new anti‐angiogenic drugs are urgently needed. Flavonoids, a class of natural compounds found in many foods, are inexpensive, widely available, and exhibit a broad range of biological activities, low toxicity, and favourable safety profiles. Several studies find that various flavonoids inhibit angiogenesis in breast cancer, indicating great therapeutic potential. In this review, we summarize the role of angiogenesis in breast cancer and the potential of natural flavonoids as anti‐angiogenic agents for breast cancer treatment. We discuss the value and significance of nanotechnology for improving flavonoid absorption and utilization and anti‐angiogenic effects, as well as the challenges of using natural flavonoids as drugs.
Accumulating evidences indicate that long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) play important roles in tumorigenesis. However, the mechanisms remain largely unknown. To explore lncRNAs and circRNAs expression profiling and their biological functions in bladder cancer, we surveyed the lncRNA/circRNA and mRNA expression profiles of bladder cancer and para-cancer tissues using microarray for four patients. Thousands of significantly changed lncRNAs and mRNAs as well as hundreds of circRNAs were identified. Five dysregulated lncRNAs and four mRNAs were confirmed by quantitative real-time PCR in 30 pairs of samples. GO and KEGG pathway enrichment analyses were executed to determine the principal functions of the significantly deregulated genes. Further more, we constructed correlated expression networks including coding-noncoding co-expression (CNC), competing endogenous RNAs (ceRNA), cis regulation, lncRNAs-transcription factor (TF)-mRNA with bioinformatics methods. Co-expression analysis showed lncRNA APLP2 expression is correlated with apoptosis-related genes, including PTEN and TP53INP1. CeRNA network inferred that lncRNA H19 and circRNA MYLK could bind competitively with miRNA-29a-3p increasing target gene DNMT3B, VEGFA and ITGB1 expressions. Moreover, the nearby genes pattern displayed that overexpressing ADAM2 and C8orf4 are cis-regulated by lncRNA RP11-359E19.2, involving in progression of bladder cancer. In addition, lncRNAs-TF-mRNA diagram indicated that lncRNA BC041488 could trans-regulate CDK1 mRNA expression through SRF transcription factor. Taken together, these results suggested lncRNAs and circRNAs could implicate in the pathogenesis and development of bladder cancer. Our findings provide a novel perspective on lncRNAs and circRNAs and lay the foundation for future research of potential roles of lncRNAs and circRNAs in bladder carcinoma.
Convolutional long and short time memory network is a kind of fusion model, which inherits the excellent spatial feature extraction ability of convolutional neural network, and can effectively complete the processing and classification of time series data by using the memory ability of long and short time memory network to historical data and the unique gating mechanism. This paper uses the human behavior data set collected by the Wireless Data Mining Laboratory (WISDM) of Fordham University to predict and classify the six daily human behaviors: walking, jogging, going upstairs, going downstairs, sitting and standing. By comparing with long and short time memory network, convolutional neural network and other deep learning models, the experimental results show that the convolutional long and short time memory network has the best performance among them, which the accuracy reaches 97.43% and has a great improvement in real-time and accuracy.
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