Pub Date : 2023-07-12eCollection Date: 2023-01-01DOI: 10.2142/biophysico.bppb-v20.0031
Tatsuya Iida, Hajime Shinoda, Rikiya Watanabe
With the recent global outbreak of COVID-19, there is an urgent need to establish a versatile diagnostic method for viral infections. Gene amplification test or antigen test are widely used to diagnose viral infections; however, these methods generally have technical drawbacks either in terms of sensitivity, accuracy, or throughput. To address this issue, we recently developed an amplification-free digital RNA detection method (SATORI), which can identify and detect viral genes at the single-molecule level in approximately 9 min, satisfying almost all detection performance requirements for the diagnosis of viral infections. In addition, we also developed practical platforms for SATORI, such as an automated platform (opn-SATORI) and a low-cost compact fluorescence imaging system (COWFISH), with the aim of application in clinical settings. Our latest technologies can be inherently applied to diagnose a variety of RNA viral infections, such as COVID-19 and Influenza A/B, and therefore, we expect that SATORI will be established as a versatile platform for point-of-care testing of a wide range of infectious diseases, thus contributing to the prevention of future epidemics. This article is an extended version of the Japanese article published in the SEIBUTSU BUTSURI Vol. 63, p. 115-118 (2023).
{"title":"SATORI: Amplification-free digital RNA detection method for the diagnosis of viral infections.","authors":"Tatsuya Iida, Hajime Shinoda, Rikiya Watanabe","doi":"10.2142/biophysico.bppb-v20.0031","DOIUrl":"10.2142/biophysico.bppb-v20.0031","url":null,"abstract":"<p><p>With the recent global outbreak of COVID-19, there is an urgent need to establish a versatile diagnostic method for viral infections. Gene amplification test or antigen test are widely used to diagnose viral infections; however, these methods generally have technical drawbacks either in terms of sensitivity, accuracy, or throughput. To address this issue, we recently developed an amplification-free digital RNA detection method (SATORI), which can identify and detect viral genes at the single-molecule level in approximately 9 min, satisfying almost all detection performance requirements for the diagnosis of viral infections. In addition, we also developed practical platforms for SATORI, such as an automated platform (opn-SATORI) and a low-cost compact fluorescence imaging system (COWFISH), with the aim of application in clinical settings. Our latest technologies can be inherently applied to diagnose a variety of RNA viral infections, such as COVID-19 and Influenza A/B, and therefore, we expect that SATORI will be established as a versatile platform for point-of-care testing of a wide range of infectious diseases, thus contributing to the prevention of future epidemics. This article is an extended version of the Japanese article published in the SEIBUTSU BUTSURI Vol. 63, p. 115-118 (2023).</p>","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"1 1","pages":"e200031"},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10728625/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89113319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Diurnal Variation in Tear Film Lipid Layer Using Smartphone-based Interferometry","authors":"Yoshiro Okazaki, Mamoru Iwabuchi, N. Yokoi","doi":"10.14326/abe.12.163","DOIUrl":"https://doi.org/10.14326/abe.12.163","url":null,"abstract":"","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67000325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Omid Jamalipournokandeh, J. Hori, K. Asakawa, K. Yana
{"title":"Dispositional Flow and Related Psychological Measures Associated with Heart Rate Diurnal Rhythm","authors":"Omid Jamalipournokandeh, J. Hori, K. Asakawa, K. Yana","doi":"10.14326/abe.12.9","DOIUrl":"https://doi.org/10.14326/abe.12.9","url":null,"abstract":"","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67000886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nene Mouri, M. Sasaki, Taichi Yagimaki, Marie Murakami, K. Igari, Keiichi Sasaki
{"title":"Development of a Training Simulator for Caregivers' Toothbrushing Skill Using Virtual Reality","authors":"Nene Mouri, M. Sasaki, Taichi Yagimaki, Marie Murakami, K. Igari, Keiichi Sasaki","doi":"10.14326/abe.12.91","DOIUrl":"https://doi.org/10.14326/abe.12.91","url":null,"abstract":"","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67000903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yota Kikuchi, Seiki Nagahori, Hironori Suzuki, Takashi Jin, Y. Nomura
{"title":"Goniometric Examination of Diffuse Reflectance of a Skin Phantom in the Wavelength Range from 400 to 1600 nm","authors":"Yota Kikuchi, Seiki Nagahori, Hironori Suzuki, Takashi Jin, Y. Nomura","doi":"10.14326/abe.12.108","DOIUrl":"https://doi.org/10.14326/abe.12.108","url":null,"abstract":"","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67000103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Y. Murayama, Aiko Uemura, M. Kitazawa, J. Toyotani, Asako Taniuchi, T. Togawa
{"title":"Determination of Biphasic Menstrual Cycle Based on the Fluctuation of Abdominal Skin Temperature during Sleep","authors":"Y. Murayama, Aiko Uemura, M. Kitazawa, J. Toyotani, Asako Taniuchi, T. Togawa","doi":"10.14326/abe.12.28","DOIUrl":"https://doi.org/10.14326/abe.12.28","url":null,"abstract":"","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"8 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67000658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Transcranial magnetic stimulation (TMS) is a widely used non-invasive neurostimulation technique in neuroscience and in the treatment of psychiatric disorders. By placing a TMS coil over a patient's head, neurons in the brain can be electromagnetically stimulated through the induction of an electric field (E-field). Accurate estimation of the E-field induced in a patient's head is crucial for determining the stimulated area of the brain. The electromagnetic simulation for E-field estimation involves two processes: the development of a volume conductor model (VCM) to determine the electrical conductivity at each position of the brain from a head magnetic resonance (MR) image, and the computation of the E-field on the VCM. Currently, neither of these processes can be performed in real-time. Achieving real-time estimation would greatly assist in determining the appropriate coil position and direction to stimulate the target regions in the patient's brain. In recent years, several methods utilizing deep neural networks (DNNs) have been proposed to estimate E-fields from MR images in real-time. These methods construct a regressor of the E-field using a set of simulated E-fields as training data to estimate the E-field. However, the reliability of these regressors in clinical applications could be improved by incorporating uncertainty estimation of the regressed variables, although this has not been reported. In this study, we enhanced the accuracy of E-field strength estimation by first regressing the E-field and then computing the norm of the E-field vectors, instead of directly regressing the E-field strength. In addition, we investigated the statistical uncertainty of the regressed E-fields using DNN. It should be noted that the E-fields estimated by the regressors are random variables. To evaluate the uncertainty of this application, we employed MCDropout, a well-known Bayesian estimation method. The uncertainty of the regressed E-field was evaluated for each anatomical tissue of the brain, to examine the relationship between uncertainty and depth from the coil. The experimental results of this evaluation are presented quantitatively.
{"title":"Electric Field Regression and Error Variance Estimation for Transcranial Magnetic Stimulation using Deep Neural Networks","authors":"Toyohiro Maki, Tatsuya Yokota, Akimasa Hirata, Hidekata Hontani","doi":"10.14326/abe.12.225","DOIUrl":"https://doi.org/10.14326/abe.12.225","url":null,"abstract":"Transcranial magnetic stimulation (TMS) is a widely used non-invasive neurostimulation technique in neuroscience and in the treatment of psychiatric disorders. By placing a TMS coil over a patient's head, neurons in the brain can be electromagnetically stimulated through the induction of an electric field (E-field). Accurate estimation of the E-field induced in a patient's head is crucial for determining the stimulated area of the brain. The electromagnetic simulation for E-field estimation involves two processes: the development of a volume conductor model (VCM) to determine the electrical conductivity at each position of the brain from a head magnetic resonance (MR) image, and the computation of the E-field on the VCM. Currently, neither of these processes can be performed in real-time. Achieving real-time estimation would greatly assist in determining the appropriate coil position and direction to stimulate the target regions in the patient's brain. In recent years, several methods utilizing deep neural networks (DNNs) have been proposed to estimate E-fields from MR images in real-time. These methods construct a regressor of the E-field using a set of simulated E-fields as training data to estimate the E-field. However, the reliability of these regressors in clinical applications could be improved by incorporating uncertainty estimation of the regressed variables, although this has not been reported. In this study, we enhanced the accuracy of E-field strength estimation by first regressing the E-field and then computing the norm of the E-field vectors, instead of directly regressing the E-field strength. In addition, we investigated the statistical uncertainty of the regressed E-fields using DNN. It should be noted that the E-fields estimated by the regressors are random variables. To evaluate the uncertainty of this application, we employed MCDropout, a well-known Bayesian estimation method. The uncertainty of the regressed E-field was evaluated for each anatomical tissue of the brain, to examine the relationship between uncertainty and depth from the coil. The experimental results of this evaluation are presented quantitatively.","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135611106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Transepidermal Water Loss Estimation Model for Evaluating Skin Barrier Function","authors":"Osamu Uehara, T. Kusuhara, Takao Nakamura","doi":"10.14326/abe.12.1","DOIUrl":"https://doi.org/10.14326/abe.12.1","url":null,"abstract":"","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67000038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zainab R. Alomari, Wasan M. Abdulatef, Mahmod A. Al-Zubaidy
Compound plane-wave imaging (CPWI) is a widely used and investigated imaging technique in medical ultrasound because it provides high quality ultrafast imaging for recent applications such as elastography. CPWI can be either coherent to provide high resolution and reduce sidelobe, or incoherent to provide high speckle homogeneity. To further improve imaging quality, coherence-based factors are used for weighting the output of ultrasound beamformers. This work studied the effects of the number of compounded frames and the step between these frames on the imaging quality produced by coherent and incoherent CPWI in the presence of the generalized coherence factor (GCF). The quality of the produced images of two different RF datasets was assessed in two different scenarios, in addition to conducting cyst phantom simulations. Results showed that the amount of image contrast improved by GCF increased, while the amount of resolution improved by GCF decreased, with the increase in step between frames. The same results were obtained in both types of CPWI. On the other hand, increasing the number of frames had almost no effect on the amounts of improvement provided by GCF. When CPWI is used in ultrafast imaging, it is important to monitor frame rates as well as imaging quality; these two factors are, respectively, inversely and directly proportional to the number of compounding frames. Therefore, the results of this research provide guidelines for accurate angle selection for CPWI so that a trade-off between imaging quality and frame rate is achieved.
{"title":"Performance Evaluation of Compound Plane-Wave Imaging Combined with the Generalized Coherence Factor","authors":"Zainab R. Alomari, Wasan M. Abdulatef, Mahmod A. Al-Zubaidy","doi":"10.14326/abe.12.204","DOIUrl":"https://doi.org/10.14326/abe.12.204","url":null,"abstract":"Compound plane-wave imaging (CPWI) is a widely used and investigated imaging technique in medical ultrasound because it provides high quality ultrafast imaging for recent applications such as elastography. CPWI can be either coherent to provide high resolution and reduce sidelobe, or incoherent to provide high speckle homogeneity. To further improve imaging quality, coherence-based factors are used for weighting the output of ultrasound beamformers. This work studied the effects of the number of compounded frames and the step between these frames on the imaging quality produced by coherent and incoherent CPWI in the presence of the generalized coherence factor (GCF). The quality of the produced images of two different RF datasets was assessed in two different scenarios, in addition to conducting cyst phantom simulations. Results showed that the amount of image contrast improved by GCF increased, while the amount of resolution improved by GCF decreased, with the increase in step between frames. The same results were obtained in both types of CPWI. On the other hand, increasing the number of frames had almost no effect on the amounts of improvement provided by GCF. When CPWI is used in ultrafast imaging, it is important to monitor frame rates as well as imaging quality; these two factors are, respectively, inversely and directly proportional to the number of compounding frames. Therefore, the results of this research provide guidelines for accurate angle selection for CPWI so that a trade-off between imaging quality and frame rate is achieved.","PeriodicalId":54017,"journal":{"name":"Advanced Biomedical Engineering","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136373575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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