A model local interpretation routine for deep learning based radio galaxy classification

Radio galaxy morphological classification is one of the critical steps when producing source catalogues for large-scale radio continuum surveys. While many recent studies attempted to classify source radio morphology from survey image data using deep learning algorithms (i.e., Convolutional Neural Networks), they concentrated on model robustness most time. It is unclear whether a model similarly makes predictions as radio astronomers did. In this work, we used Local Interpretable Model-agnostic Explanation (LIME), an state-of-the-art eXplainable Artificial Intelligence (XAI) technique to explain model prediction behaviour and thus examine the hypothesis in a proof-of-concept manner. In what follows, we describe how \textbf{LIME} generally works and early results about how it helped explain predictions of a radio galaxy classification model using this technique.Comment: 4 pages, 1 figure, accepted summary paper for URSI GASS 2023 J0

Lnc-PLA2G4A-4 facilitates the progression of hepatocellular carcinoma by inducing versican expression via sponging miR-23b-3p

Aberrant expression of long non-coding RNAs (lncRNAs) is associated with progression of multiple human cancers including hepatocellular carcinoma (HCC). However, the role of lncRNAs in HCC is not been fully understood. Our study aimed to investigate the biological function and potential molecular mechanism of Lnc-PAL2G4A-4 in HCC. In the current study, we show that Lnc-PLA2G4A-4 was significantly up-regulated in HCC tissues and high Lnc-PLA2G4A-4 expression was remarkably associated with tumor size, microvascular invasion and poor prognosis of HCC patients. Functionally, Lnc-PLA2G4A-4 positively regulated cell proliferation, invasion and migration in vitro, and facilitated lung metastasis of HCC in vivo. Mechanistically, Lnc-PLA2G4A-4 functioned as a competing endogenous RNA (ceRNA) to bind to miR-23b-3p and subsequently facilitate miR-23b-3p's target gene versican (VCAN) expression in HCC cells. Over-expression of miR-23b-3p could reverse Lnc-PLA2G4A-4 induced cell phenotypes in HCC and suppress versican expression of by rescue analysis. Collectively, Lnc-PLA2G4A-4 promotes HCC progression by targeting the miR-23b-3p/versican axis, which may be a potential biomarker and therapeutic target for HCC