Esophageal squamous cell carcinoma (ESCC) is one of the deadliest malignant diseases. Multiple studies with large clinic-based cohorts have revealed that variations of phospholipase C epsilon 1 (PLCE1) correlate with esophageal cancer susceptibility. However, the causative role of PLCE1 in ESCC has remained elusive. Here, we observed that hypomethylation-mediated upregulation of PLCE1 expression was implicated in esophageal carcinogenesis and poor prognosis in ESCC cohorts. PLCE1 inhibited cell autophagy and suppressed the protein expression of p53 and various p53-targeted genes in ESCC. Moreover, PLCE1 decreased the half-life of p53 and promoted p53 ubiquitination, whereas it increased the half-life of mouse double minute 2 homolog (MDM2) and inhibited its ubiquitination, leading to MDM2 stabilization. Mechanistically, the function of PLCE1 correlated with its direct binding to both p53 and MDM2, which promoted MDM2-dependent ubiquitination of p53 and subsequent degradation in vitro. Consequently, knockdown of PLCE1 combined with transfection of a recombinant adenoviral vector encoding wild-type p53 resulted in significantly increased levels of autophagy and apoptosis of esophageal cancer in vivo. Clinically, the upregulation of PLCE1 and mutant p53 protein predicted poor overall survival of patients with ESCC, and PLCE1 was positively correlated with p53 in ESCC cohorts. Collectively, this work identified an essential role for PLCE1- and MDM2-mediated ubiquitination and degradation of p53 in inhibiting ESCC autophagy and indicates that targeting the PLCE1–MDM2–p53 axis may provide a novel therapeutic approach for ESCC.
Significance:
These findings identify hypomethylation-mediated activation of PLCE1 as a potential oncogene that blocks cellular autophagy of esophageal carcinoma by facilitating the MDM2-dependent ubiquitination of p53 and subsequent degradation.
Towards the formalization of ontological methodologies for dynamic machine learning and semantic analyses, a new form of denotational mathematics known as concept algebra is introduced. Concept Algebra (CA) is a denotational mathematical structure for formal knowledge representation and manipulation in machine learning and cognitive computing. CA provides a rigorous knowledge modeling and processing tool, which extends the informal, static, and application-specific ontological technologies to a formal, dynamic, and general mathematical means. An operational semantics for the calculus of CA is formally elaborated using a set of computational processes in real-time process algebra (RTPA). A case study is presented on how machines, cognitive robots, and software agents may mimic the key ability of human beings to autonomously manipulate knowledge in generic learning using CA. This work demonstrates the expressive power and a wide range of applications of CA for both humans and machines in cognitive computing, semantic computing, machine learning, and computational intelligence.
Icicle will cause serious distortion of insulator electric field, weaken its voltage strength, and easily cause insulator flashover. Previous studies have shown that the longer the length of icicles on insulator, the greater the possibility of electric flashover. Then, it is of great theoretical significance and practical value to study the image identification technology of icicle length of iced insulators. Firstly, the growth mechanism and structural characteristics of insulator icicles are discussed in this paper, and the image acquisition method of iced insulator is discussed. Secondly, the methods of saliency detection and color feature analysis are used to extract the region of icicle and insulator sheds respectively, then, the icicle structure on insulator is obtained by the difference calculation of above two images. Meanwhile, the pixel curve of the iced insulator image is processed by Fourier transform, and the reference size of insulators icicle is obtained by calculating the length of the shed spacing. Finally, a practical case about iced insulators in substations is analyzed in detail, which proves the effectiveness of the method proposed in this paper.
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