Zebrafish an emerging animal model for studies comparability with humans, good accessibility to the hearing utilize this animal model, methodologies need to be used to on auditory system. This model presents high org...Zebrafish an emerging animal model for studies comparability with humans, good accessibility to the hearing utilize this animal model, methodologies need to be used to on auditory system. This model presents high organ, and high throughput capacity. To better quantify the hearing function of the zebrafish. Zebrafish displays a series of innate and robust behavior related to its auditory function. Here, we reviewed the advantage of using zebrafish in auditory research and then introduced three behavioral tests, as follows： the startle response, the vestibular-ocular reflex, and rheotaxis. These tests are discussed in terms of their physiological characteristics, up-to-date technical development, and apparatus description. Test limitation and areas to improve are also introduced. Finally, we revealed the feasibility of these applications in zebrafish behavioral assessment and their potential in the high-throughput screening on hearing-related genes and drugs.展开更多
The hypothesis of behavioral parameters dependence measured from person’s head movements in quasi-stationary state on COVID-19 disease is discussed. Method for determining the dependence of vestibular-emotional refle...The hypothesis of behavioral parameters dependence measured from person’s head movements in quasi-stationary state on COVID-19 disease is discussed. Method for determining the dependence of vestibular-emotional reflex parameters on COVID-19, various diseases and pathologies are proposed. Micro-movements of a head for representatives of the control group (with a confirmed absence of COVID-19 disease) and a group of patients with a confirmed diagnosis of COVID-19 were studied using vibraimage technology. Parameters and criteria for the diagnosis of COVID-19 for training artificial intelligence (AI) on the control group and the patient group are proposed. 3-layer (one hidden layer) feedforward neural network (40 + 20 + 1 sigmoid neurons) was developed for AI training. AI was firstly trained on the primary sample of patients and a control group. Study of a random sample of people with trained AI was carried out and the possibility of detecting COVID-19 using the proposed method was proved a week before the onset of clinical symptoms of the disease. Number of COVID-19 diagnostic parameters was increased to 26 and AI was trained on a sample of 536 measurements, 268 patient measurement results and 268 measurement results in the control group. The achieved diagnostic accuracy was more than 99%, 4 errors per 536 measurements (2 false positive and 2 false negative), specificity 99.25% and sensitivity 99.25%. The issues of improving the accuracy and reliability of the proposed method for diagnosing COVID-19 are discussed. Further ways to improve the characteristics and applicability of the proposed method of diagnosis and self-diagnosis of COVID-19 are outlined.展开更多
文摘Zebrafish an emerging animal model for studies comparability with humans, good accessibility to the hearing utilize this animal model, methodologies need to be used to on auditory system. This model presents high organ, and high throughput capacity. To better quantify the hearing function of the zebrafish. Zebrafish displays a series of innate and robust behavior related to its auditory function. Here, we reviewed the advantage of using zebrafish in auditory research and then introduced three behavioral tests, as follows： the startle response, the vestibular-ocular reflex, and rheotaxis. These tests are discussed in terms of their physiological characteristics, up-to-date technical development, and apparatus description. Test limitation and areas to improve are also introduced. Finally, we revealed the feasibility of these applications in zebrafish behavioral assessment and their potential in the high-throughput screening on hearing-related genes and drugs.
文摘The hypothesis of behavioral parameters dependence measured from person’s head movements in quasi-stationary state on COVID-19 disease is discussed. Method for determining the dependence of vestibular-emotional reflex parameters on COVID-19, various diseases and pathologies are proposed. Micro-movements of a head for representatives of the control group (with a confirmed absence of COVID-19 disease) and a group of patients with a confirmed diagnosis of COVID-19 were studied using vibraimage technology. Parameters and criteria for the diagnosis of COVID-19 for training artificial intelligence (AI) on the control group and the patient group are proposed. 3-layer (one hidden layer) feedforward neural network (40 + 20 + 1 sigmoid neurons) was developed for AI training. AI was firstly trained on the primary sample of patients and a control group. Study of a random sample of people with trained AI was carried out and the possibility of detecting COVID-19 using the proposed method was proved a week before the onset of clinical symptoms of the disease. Number of COVID-19 diagnostic parameters was increased to 26 and AI was trained on a sample of 536 measurements, 268 patient measurement results and 268 measurement results in the control group. The achieved diagnostic accuracy was more than 99%, 4 errors per 536 measurements (2 false positive and 2 false negative), specificity 99.25% and sensitivity 99.25%. The issues of improving the accuracy and reliability of the proposed method for diagnosing COVID-19 are discussed. Further ways to improve the characteristics and applicability of the proposed method of diagnosis and self-diagnosis of COVID-19 are outlined.
