作者
Liujing Zhuang,Mengxue Liu,Nan Jiang,Xinwei Wei,Yuxiang Pan,Yiqun Yu,Píng Wang
摘要
The mammalian olfactory system enables to sense and distinguish a large number of odors, which is essential to find food, avoid predators, communicate and reproduce, while the human olfactory system can even avoid potential hazard by discriminating the smell quality. Olfactory dysfunction is a common disease symptom which seriously affects the life quality of patients. In addition, many studies have revealed that olfactory dysfunction can also indicate many other potential diseases, such as neurodegenerative diseases and mental diseases. Olfactory dysfunction is an early common symptom of a variety of diseases, such as inflammation, viral infection, neurodegenerative diseases, and the current epidemic of COVID-19. Researchers have indicated that some patients with certain diseases already have suffered from symptoms of olfactory dysfunction early in the clinic. For instance, one of the early clinical symptoms of SARS-CoV-2 virus infection is the loss of smell. Besides, patients suffered from Alzheimer's disease and Parkinson's disease usually have an increased threshold of olfactory perception and even endure anosmia. Therefore, research on early screening and diagnosis of dysosmia diseases on the basis of olfactory function detection is of great significance to control and slow the disease's progression and to improve the health of human body. At present, olfactory function detection technologies mainly contain olfactory neuropsychological testing, electrophysiological detection, olfaction system structure or functional imaging, etc. Although these technologies have played an important role in the study of dysosmia, there have been no standardized detection indicators established so far. Therefore, the establishment and improvement of early olfactory dysfunction disease diagnosis technology based on the detection of olfactory function requires a novel approach in principle and technology. By utilizing the bionic olfactory sensing technologies such as bioelectronic noses, the olfactory analog sensing system with high sensitivity, high specificity and short response time, and even simulating biological olfactory systems, can be expected to be realized. Based on the current understanding of the mechanism of olfactory dysfunction, our team is committed to breaking through the traditional odor-induced olfactory function detection method. By combining with the bionic olfactory perception technology, three original methods which include olfactory neural network chip, organoid chip and neural interactive olfaction detection technology have been proposed. These three technologies essentially construct and simulate the olfactory nervous system in vitro or in vivo, by means of the sensing technique to detect physiological signals changes that correspond with the alternations in the nervous system. However, the difficulties currently lie in how to determine the characteristic physiological signal, and how to establish the correlation between the characteristic signals and the degree of dysosmia for the ultimate goal of further screening the olfactory dysfunction related diseases through the detection parameters. The clarification of these difficulties and in-depth progress of research will promote the innovation and development of olfactory function detection technology, and provide reliable theoretical technical support and experimental basis. This review comprehensively interpreted the current research status of dysosmia diseases, as well as analyzed the principles of bionic olfactory perception technology and its research progress in the detection and diagnosis of dysosmia and related diseases. With the development of multidisciplinary intersection in the field of biomedical engineering, the transformation and application of cell network chips, organoid bionic chips and braincomputer interaction technology will promote the progress of bionic olfactory perception technology in the research of olfactory dysfunction diseases and the innovation of clinical diseases diagnosis. © 2021, Science Press. All right reserved.