New insight into circRNAs: characterization, strategies, and biomedical applications.

Exp Hematol Oncol

MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, People's Republic of China.

Published: October 2023

Circular RNAs (circRNAs) are a class of covalently closed, endogenous ncRNAs. Most circRNAs are derived from exonic or intronic sequences by precursor RNA back-splicing. Advanced high-throughput RNA sequencing and experimental technologies have enabled the extensive identification and characterization of circRNAs, such as novel types of biogenesis, tissue-specific and cell-specific expression patterns, epigenetic regulation, translation potential, localization and metabolism. Increasing evidence has revealed that circRNAs participate in diverse cellular processes, and their dysregulation is involved in the pathogenesis of various diseases, particularly cancer. In this review, we systematically discuss the characterization of circRNAs, databases, challenges for circRNA discovery, new insight into strategies used in circRNA studies and biomedical applications. Although recent studies have advanced the understanding of circRNAs, advanced knowledge and approaches for circRNA annotation, functional characterization and biomedical applications are continuously needed to provide new insights into circRNAs. The emergence of circRNA-based protein translation strategy will be a promising direction in the field of biomedicine.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10568798PMC
http://dx.doi.org/10.1186/s40164-023-00451-wDOI Listing

Publication Analysis

Top Keywords

biomedical applications
12
characterization circrnas
8
circrnas
7
insight circrnas
4
characterization
4
circrnas characterization
4
characterization strategies
4
strategies biomedical
4
applications circular
4
circular rnas
4

Similar Publications

Liquid-Metal-Based Multichannel Strain Sensor for Sign Language Gesture Classification Using Machine Learning.

ACS Appl Mater Interfaces

January 2025

Centre for Robotics and Automation, Department of Biomedical Engineering, City University of Hong Kong, Hong Kong 999077, China.

Liquid metals are highly conductive like metallic materials and have excellent deformability due to their liquid state, making them rather promising for flexible and stretchable wearable sensors. However, patterning liquid metals on soft substrates has been a challenge due to high surface tension. In this paper, a new method is proposed to overcome the difficulties in fabricating liquid-state strain sensors.

View Article and Find Full Text PDF

Normalization Based on Shift and Ion Intensity in SALDI-TOFMS Imaging of Samples with Non-Horizontal Surface.

Mass Spectrom (Tokyo)

December 2024

Department of Pharmaceutical Engineering, Faculty of Engineering, Toyama Prefectural University, 5180 Kurokawa, Imizu-City, Toyama 939-0398, Japan.

Matrix-assisted laser desorption/ionization (MALDI), surface-assisted laser desorption/ionization (SALDI), and time-of-flight mass spectrometry (TOFMS) imaging are used for visualizing the spatial distribution of analytes. Mass spectrometry (MS) imaging of a sample with a rough surface with a uniform distribution of an analyte does not provide uniform ion intensities in the image. A shift in the value of the analyte ions is also observed.

View Article and Find Full Text PDF

The p53-MDM2 pathway plays a crucial role regulating tumor suppression and is a focal point of cancer research. This literature review delves into the complex interplay between the tumor suppressor protein p53 and its main regulator MDM2, highlighting their interaction and implications in cancer development and progression. The review compiles and summarizes the existing understanding of the biology and regulation of p53 and MDM2, emphasizing their roles in various cellular processes, including cell cycle regulation, DNA repair, apoptosis, and metabolism.

View Article and Find Full Text PDF

In this work, a cost-effective, scalable pneumatic silicone actuator array is introduced, designed to dynamically conform to the user's skin and thereby alleviate localised pressure within a prosthetic socket. The appropriate constitutive models for developing a finite element representation of these actuators are systematically identified, parametrised, and validated. Employing this computational framework, the surface deformation fields induced by 270 variations in soft actuator array design parameters under realistic load conditions are examined, achieving predictive accuracies within 70 µm.

View Article and Find Full Text PDF

Recent advancements in large language models (LLMs) like ChatGPT and LLaMA have shown significant potential in medical applications, but their effectiveness is limited by a lack of specialized medical knowledge due to general-domain training. In this study, we developed Me-LLaMA, a new family of open-source medical LLMs that uniquely integrate extensive domain-specific knowledge with robust instruction-following capabilities. Me-LLaMA comprises foundation models (Me-LLaMA 13B and 70B) and their chat-enhanced versions, developed through comprehensive continual pretraining and instruction tuning of LLaMA2 models using both biomedical literature and clinical notes.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!