Circular RNAs (circRNAs) are a class of noncoding RNAs that regulate gene expression at the posttranscriptional level. The specific functions of circRNAs in ovarian cancer are yet to be established. Previous sequencing analyses have revealed an abnormal expression of hsa_circ_0061140 in ovarian cancer. The main aim of the present study is to establish the specific role of hsa_circ_0061140 in ovarian cancer. circRNA expression in ovarian cancer cells was detected via real-time qPCR. The effects on specific cellular characteristics (proliferation, migration, and the EMT) and subcellular localization of hsa_circ_0061140 were assessed via RNA fluorescence in situ hybridization, knockdown, and luciferase reporter assays in the SKOV3 and A2780 cell lines. Tumorigenesis was induced in nude mice to assess the effects of hsa_circ_0061140 on ovarian cancer growth in vivo. Our results showed that hsa_circ_0061140 was upregulated in ovarian cancer cell lines. Knockdown of hsa_circ_0061140 suppressed cell proliferation and migration, both in vivo and in vitro, by inhibiting FOXM1 expression through sponging miR-370. Overexpression of FOXM1 or suppression of miR-370 rescued hsa_circ_0061140 silencing-induced inhibition of cell proliferation, migration, and the EMT. The associations among hsa_circ_0061140, miR-370, and FOXM1 were confirmed via bioinformatic prediction and fluorescein reporter experiments. Thus, hsa_circ_0061140 appeared to function as a competing endogenous RNA of miR-370 that promoted cell growth and metastasis in ovarian cancer through regulation of the miR-370/FOXM1 pathway mediating EMT.

Neuromorphic computation, which emulates the signal process of the human brain, is considered to be a feasible way for future computation. Realization of dynamic modulation of synaptic plasticity and accelerated learning, which could improve the processing capacity and learning ability of artificial synaptic devices, is considered to further improve energy efficiency of neuromorphic computation. Nevertheless, realization of dynamic regulation of synaptic weight without an external regular terminal and the method that could endow artificial synaptic devices with the ability to modulate learning speed have rarely been reported. Furthermore, finding suitable materials to fully mimic the response of photoelectric stimulation is still challenging for photoelectric synapses. Here, a floating gate synaptic transistor based on an L-type ligand-modified all-inorganic CsPbBr 3 perovskite quantum dots is demonstrated. This work provides first clear experimental evidence that the synaptic plasticity can be dynamically regulated by changing the waveforms of action potential and the environment temperature and both of these parameters originate from and are crucial in higher organisms. Moreover, benefiting from the excellent photoelectric properties and stability of quantum dots, a temperature-facilitated learning process is illustrated by the classical conditioning experiment with and without illumination, and the mechanism of synaptic plasticity is also demonstrated. This work offers a feasible way to realize dynamic modulation of synaptic weight and accelerating the learning process of artificial synapses, which showed great potential in the reduction of energy consumption and improvement of efficiency of future neuromorphic computing.

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Optical memory based on a vertical organic field effect transistor with ultrashort channel length exhibits excellent device performance with distinct storage levels.