Objective To review the lately new progress of fish collagen as biomedical materials, and then analyze feasibility and risk management of its application as a substitute of collagen originated from mammals in clinical practice. Methods Based on extensive research on new application and investigation of fish collagen, the paper was prepared to bring comprehensive analysis of its research and application status, and then several key points were focused on. Results Fish collagen has been proved to be a novel collagen of rich source, low risk of virus transmission, low biological risk, less religious barrier, and high biocompatibility. Fish collagen has promising prospect when applied in clinical practice as novel collagen especially as a substitute of collagen derived from mammals. However, very few related translational medicine research of fish collagen has been reported up to now in China. Conclusion As a novel potential substitute of collagen source derived from mammals, fish collagen is concerned to be clinical feasible and necessary in translational medicine. However, massive applied basic researches should be focused on in the further investigations.
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.
Bionic untethered micro-nano robots, due to their advantages of small size, low weight, large thrust-to-weight ratio, strong wireless mobility, high flexibility and high sensitivity, have very important application values in the fields of biomedicine, such as disease diagnosis, minimally invasive surgery, targeted therapy, etc. This review article systematically introduced the manufacturing methods and motion control, and discussed the biomedical applications of bionic untethered micro-nano robots. Finally, the article discussed the possible challenges for bionic untethered micro-nano robots in the future. In summary, this review described bionic untethered micro-nano robots and their potential applications in biomedical fields.
【Abstract】ObjectiveTo study the applicatble value of absorbable biomedical membrane (ABMM) in thyroid operation.MethodsABMM (size 0.02 cm) was placed between trachea and the skin flap trachea and the anterior muscles of the neck, and between anterior muscles of neck and the skin flap after radical cure for thyroid cancer of thyroidectomy including one or two lobes. ResultsConglutination under the incision was significantly lighter in experiment group (153 cases ) than control group (139 cases) ( P＜0.05）, but the difference of complication between two groups was insignificant after postoperative followup for 6 weeks. ConclusionABMM can effectively prevent conglutination under the incision without increasing of postoperative complications.
Through magnetic resonance electrical properties tomography (MR-EPT), electrical conductivity and permittivity of biological tissues could be reconstructed based on radio frequency field of magnetic resonance imaging (MRI) system. High precision and high resolution image could be obtained without current injection. In this study, XFDTD software was used to establish a finite element model of the human breast. Simulation was delivered at the Larmor frequency of 128 MHz by a 16-channel radio frequency coil. Conductivity and permittivity of the mammary tissue was reconstructed according to the B1+ field's amplitude and phase of forward problem. Anti-noise performance of the algorithm was studied by adding noise to B1+ field. The conductivity and permittivity's average relative error between simulation results and dielectric constant was 4.71% and 11.32%, respectively. With a signal-to-noise ratio of >30 dB, the noise added would not affect imaging results. This study demonstrated that high precision and high resolution image could be obtained by MR-EPT without excitation. MR-EPT had excellent feasibility and developing potential in early detection of diseases.
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.
This paper provides a brief overview of the current research activities which focused on the bio-application of gold magnetic nanocomposite particles. By combining the magnetic characteristics of the iron oxide core with the unique features of nano-gold particles such as targeting by surface modification and optical properties, such composite nanoparticles have a wide range of applications in cancer hyperthermia, CT and MRI imaging, bio-separation, biosensors, gene diagnosis, drug targeting and many other biomedical fields.
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.
Traditional biomedical data analysis technology faces enormous challenges in the context of the big data era. The application of deep learning technology in the field of biomedical analysis has ushered in tremendous development opportunities. In this paper, we reviewed the latest research progress of deep learning in the field of biomedical data analysis. Firstly, we introduced the deep learning method and its common framework. Then, focusing on the proposal of biomedical problems, data preprocessing method, model building method and training algorithm, we summarized the specific application of deep learning in biomedical data analysis in the past five years according to the chronological order, and emphasized the application of deep learning in medical assistant diagnosis. Finally, we gave the possible development direction of deep learning in the field of biomedical data analysis in the future.
In recent years, the technologies based on the electrical properties (EPs) of human tissue, such as electrical impedance tomography (EIT) and magnetic resonance electrical impedance tomography (MREIT), have become one of the most popular research subjects in biomedicine. Compared with EIT and MREIT, the magnetic resonance electrical property tomography (MR-EPT) is a new technique using nondestructive EPs method. MR-EPT reconstructs the electrical conductivity and permittivity of the biological tissues based on the radio frequency field of the magnetic resonance imaging (MRI) system. It can obtain an accurate and high resolution image without current injection. In this paper, several methods for the EPs are reviewed, especially the MR-EPT. The theory, advantages and prospects of MR-EPT's are elaborated. The method of specific absorption rate (SAR) based on it is also introduced. MR-EPT is deserved further research and should be given more attention by the researchers. All this evolution based on MREPT can give new energy to the medical diagnosis.