Publications by authors named "Linghui Zhong"
Article Synopsis
- * Recent studies show that these micropeptides play crucial roles in several bodily functions, such as regulating homeostasis, inflammation, metabolism, and tumor progression, rather than lncRNAs themselves.
- * The review discusses advancements in computational methods for predicting lncRNA functions and emphasizes the potential of lncRNA-encoded micropeptides as therapeutic targets in cancer treatment.
p53-regulated lncRNAs in cancers: from proliferation and metastasis to therapy.
Cancer Gene Ther
November 2023
Long non-coding RNAs (lncRNAs) have been identified as master gene regulators through various mechanisms such as transcription, translation, protein modification and RNA-protein complexes. LncRNA dysregulation is frequently associated with a variety of biological functions and human diseases including cancer. The p53 network is a key tumor-suppressive mechanism that transcriptionally activates target genes to suppress cellular proliferation in human malignancies.
View Article and Find Full Text PDFLung cancer is the leading cause of cancer-related deaths worldwide. KRAS is the main oncogenic driver in lung cancer that can be activated by gene mutation or amplification, but whether long non-coding RNAs (lncRNAs) regulate its activation remains unknown. Through gain and loss of function approaches, we identified that lncRNA HIF1A-As2, a KRAS-induced lncRNA, is required for cell proliferation, epithelial-mesenchymal transition (EMT) and tumor propagation in non-small cell lung cancer (NSCLC) in vitro and in vivo.
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- Malignant cutaneous melanoma is a highly lethal skin cancer that is diagnosed through skin biopsies, but digital imaging techniques can aid in decision-making for biopsies.
- The study hypothesized that a computer tool could distinguish between malignant and benign pigmented skin lesions using advanced image processing methods.
- The developed prediction model analyzed lesions based on shape, border, and color, achieving a 77% accuracy rate, which improves upon traditional examination methods by professionals in identifying melanoma.
Feature attraction and classification of mental EEG using approximate entropy.
Conf Proc IEEE Eng Med Biol Soc
September 2008
The approximate entropy (ApEn), which is a new statistical method to measure the complexity of sequences, was introduced in this paper. First, the EOG artifact was removed from the EEG using the method of independent component analysis (ICA). Then ApEn was used to analyze the mental EEG signals to extract the features for pattern identification and task classification.
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