The present paper is to evaluate the scientific research level and development trends of biomedical engineering in China using metrology analysis on Chinese biomedical engineering scientific literatures. Pubmed is used to search the biomedical engineering publications in recent 5 years which are indexed by Science Citation Index, and the number and cited times of these publications and the impact factor of the journals are analyzed. The results show that comparing with the world, although the number of the publication in China has increased in recent 5 years, there is still much room for improvement. Among Chinese mainland, Hongkong and Taiwan, Chinese mainland maintains the obvious advantage in this subject, but Hongkong has the highest average cited number. Shanghai and Beijing have better research ability than other areas in Chinese mainland.
Circular RNA (circRNA) is a type of single-stranded RNA that binds in a closed loop structure by covalent bond. It is highly expressed and has diverse functions in the eukaryotic transcriptome, and it also has the potential to regulate the process of cell differentiation. Stem cells are important seed cells and common research tools in the field of tissue engineering, which have multi-directional differentiation potential and low immunogenicity. Its clinical application for the treatment of diseases has broad prospects, and the research on their differentiation mechanism has gradually penetrated to the molecular level. A number of studies have shown that circRNA participates in stem cell differentiation and plays a key role through a variety of pathways. This article focuses on the expression changes of circRNA during stem cell differentiation and its research advancement in regulating the differentiation mechanism of various stem cells. The review also prospects its possible role in tissue regeneration and repair, in order to further study the molecular mechanism of circRNA involved in stem cell differentiation and provide ideas for clinical practice of stem cells in biomedical engineering.
The outbreak of pneumonia caused by novel coronavirus (COVID-19) at the end of 2019 was a major public health emergency in human history. In a short period of time, Chinese medical workers have experienced the gradual understanding, evidence accumulation and clinical practice of the unknown virus. So far, National Health Commission of the People’s Republic of China has issued seven trial versions of the “Guidelines for the Diagnosis and Treatment of COVID-19”. However, it is difficult for clinicians and laymen to quickly and accurately distinguish the similarities and differences among the different versions and locate the key points of the new version. This paper reports a computer-aided intelligent analysis method based on machine learning, which can automatically analyze the similarities and differences of different treatment plans, present the focus of the new version to doctors, reduce the difficulty in interpreting the “diagnosis and treatment plan” for the professional, and help the general public better understand the professional knowledge of medicine. Experimental results show that this method can achieve the topic prediction and matching of the new version of the program text through unsupervised learning of the previous versions of the program topic with an accuracy of 100%. It enables the computer interpretation of “diagnosis and treatment plan” automatically and intelligently.