Anisotropic Signal Processing with Trigonal Selenium Nanosheet Synaptic Transistors.

Hardware implementation of an artificial neural network requires neuromorphic devices to process information with low energy consumption and high heterogeneity. Here we demonstrate an electrolyte-gated synaptic transistor (EGT) based on a trigonal selenium (t-Se) nanosheet. Due to the intrinsic low conductivity of the Se channel, the t-Se synaptic transistor exhibits ultralow energy consumption, less than 0.1 pJ per spike. More importantly, the intrinsic low symmetry of t-Se offers a strong anisotropy along its c- and a-axis in electrical conductance with a ratio of up to 8.6. The multiterminal EGT device exhibits an anisotropic response of filtering behavior to the same external stimulus, which enables it to mimic the heterogeneous signal transmission process of the axon-multisynapse biostructure in the human brain. The proof-of-concept device in this work represents an important step to develop neuromorphic electronics for processing complex signals.

ZMYND8 expression combined with pN and pM classification as a novel prognostic prediction model for colorectal cancer: Based on TCGA and GEO database analysis.

BACKGROUND: Zinc finger MYND (Myeloid, Nervy and DEAF-1)-type containing 8 (ZMYND8) is closely correlated with tumor proliferation and invasiveness. However, its prognostic value has not been estimated in colorectal cancer (CRC). OBJECTIVE: We aimed to elucidate the prognostic significance of ZMYND8 expression and the pN and pM classification supplemented by its expression in CRCs. METHODS: The candidate gene ZMYND8 is identified by TCGA database and GEO database, and then we retrospectively evaluated the status and prognostic significance of ZMYND8 expression of 174 patients with CRC. RESULTS: Online data showed high expression of ZMYND8 is closely correlated with worse overall survival. Our study revealed high expression of ZMYND8 in CRC patients was significantly associated with worse overall and disease-free survival (P< 0.05), and was an independently adverse prognostic factor for overall survival (P< 0.001) and disease-free survival (P= 0.001) by univariate and multivariate analysis. C-index to combined prognostic model containing the pN, pM classification supplemented by the status of ZMYND8 expression showed improved predictive ability comparing with the pN and pM classification model (C-index of 0.597 vs. 0.545, respectively). CONCLUSION: The combined prognostic model could improve the ability to determine the clinical outcome of patients with CRC.