Long Non-Coding RNA: Multiple Effects on the Differentiation, Maturity and Cell Function of Dendritic Cells

Xinyu Liu,Yuanheng Li,Xiaoying Jiang, Yu'en Deng, Chuanwei Ma,Qiongfang Yu,Dian Gao

Clinical Immunology（2022）SCI 3区

Nanchang Univ

Cited 10|Views25

Abstract

Long non-coding RNAs (LncRNAs), lacking protein-coding function, modulate immune function by regulating the expression of genes or the function of protein molecules. They participate in epigenetic regulation, interfere with downstream gene transcription acting as a molecular sponge to affect miRNA function, and can combine with proteins to form nucleic acid protein complexes that affect protein function or cell location to regulate genes and regulate immune function. LncRNAs are differentially expressed in immune cells. They affect the maturity, differentiation and activation of immune cells and regulate cytokine release and immune phenotype. They are closely related to immune tolerance and cell migration. Dendritic cells (DCs) are important immune cells with the most robust antigen-presenting function, and have irreplaceable roles in human innate immunity and adaptive immunity. Emerging evidence over the past few years has suggested that LncRNAs influence the differentiation and maturation of DCs and serve as a critical role in the cell phenotype and immune function of DCs. To further understand the role of LncRNAs in the occurrence and development of DC-related diseases, we elaborated the role of LncRNAs in DC immune function, including antigen presentation, T cell activation and proliferation, DC migration. Furthermore, we summarized the impact of pathological factors (tumors, inflammation, autoimmune disease, viral infection) and physiological factors (e.g., age) on the LncRNAs in DCs, and how the changed LncRNAs altered the function and behavior of DCs resulting from the intervention. We hope this review give us have a better understanding of multiple effects of LncRNA on cell function in DCs.

Translated text

Key words

LncRNAs,Dendritic cells,Regulatory function,Differentiation,Immune function

Bibtex

AI Read Science

AI Summary

AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.

Example

Background

Key content

Introduction

Methods

Results

Related work

Fund

Key content

Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

Try using models to generate summary,it takes about 60s

Must-Reading Tree

Example

Generate MRT to find the research sequence of this paper