Search

Your search keyword '"Uranaka, Tsukasa"' showing total 22 results
Start Over Author "Uranaka, Tsukasa"
22 results on '"Uranaka, Tsukasa"'

1. A Randomized Crossover Study in Single-Sided Deafness Comparing a Cartilage Conduction CROS System and an Air-Conduction CROS System

Author

Takaki, Ken, primary, Kashio, Akinori, additional, Nozaki, Etsushi, additional, Kanai, Tomomi, additional, Kamogashira, Teru, additional, Saze, Fumikazu, additional, Uranaka, Tsukasa, additional, Urata, Shinji, additional, Koyama, Hajime, additional, Kawahara, Yoshihiro, additional, and Yamasoba, Tatsuya, additional

Published
2024
Full Text
View/download PDF

2. asEars: Designing and Evaluating the User Experience of Wearable Assistive Devices for Single-Sided Deafness

Author

Takaki, Ken, primary, Nozaki, Etsushi, additional, Kanai, Tomomi, additional, Hautasaari, Ari, additional, Kashio, Akinori, additional, Sato, Daisuke, additional, Kamogashira, Teru, additional, Uranaka, Tsukasa, additional, Urata, Shinji, additional, Koyama, Hajime, additional, Yamasoba, Tatsuya, additional, and Kawahara, Yoshihiro, additional

Published
2023
Full Text
View/download PDF

3. Application of Machine Learning to Predict Hearing Outcomes of Tympanoplasty.

Author

Koyama, Hajime, Kashio, Akinori, Uranaka, Tsukasa, Matsumoto, Yu, and Yamasoba, Tatsuya

Abstract

Objective: This retrospective study aimed to evaluate the performance of machine learning techniques in predicting air‐bone gap after tympanoplasty compared with conventional scoring models and to identify the influential factors. Methods: We reviewed the charts of 105 patients (114 ears) with chronic otitis media who underwent tympanoplasty. Two numerical scoring systems (middle ear risk index [MERI] and ossiculoplasty outcome parameter staging [OOPS]) and three algorithms (random forest [RF], support vector machine [SVM], and k nearest neighbor [kNN]) were created. Experimental variables included age, preoperative air‐bone gap, soft‐tissue density lesion in the tympanic cavity in CT, otorrhea, surgical history, ossicular bone problems in CT, tympanic perforation location, perforation type (central or marginal), grafting material, smoking history, endoscopy use, and the operator whose experience was 20 years or longer, or shorter. Binary classification, postoperative air‐bone gap ≤15 or >15 dB, and multiclass classification, classification into seven categories by 10 dB, were performed, and the percentages of correct prediction were calculated. The importance of features in the RF model was calculated to identify influential factors. Results: The percentages of correct prediction in binary classification were 62.3%, 72.8%, 81.5%, 81.5%, and 81.5% in MERI, OOPS, RF, SVM, and kNN, respectively, and those in multiclass classification were 29.8%, 21.9%, 63.1%, 44.7%, and 50% in the same order. The RF model suggested larger preoperative air‐bone gap, and older age could make the postoperative air‐bone gap larger. Conclusion: The machine learning techniques, especially the RF model, are promising methods for precise postoperative air‐bone gap prediction. Level of Evidence: 4 Laryngoscope, 133:2371–2378, 2023 [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

5. Evidence for the spread of SARS-CoV-2 and olfactory cell lineage impairment in close-contact infection Syrian hamster models

Author

Ueha, Rumi, primary, Ito, Toshihiro, additional, Ueha, Satoshi, additional, Furukawa, Ryutaro, additional, Kitabatake, Masahiro, additional, Ouji-Sageshima, Noriko, additional, Uranaka, Tsukasa, additional, Tanaka, Hirotaka, additional, Nishijima, Hironobu, additional, Kondo, Kenji, additional, and Yamasoba, Tatsuya, additional

Published
2022
Full Text
View/download PDF

19. Expression of ACE2, TMPRSS2, and Furin in Mouse Ear Tissue, and the Implications for SARS‐CoV‐2 Infection.

Author

Uranaka, Tsukasa, Kashio, Akinori, Ueha, Rumi, Sato, Taku, Bing, Han, Ying, Gao, Kinoshita, Makoto, Kondo, Kenji, and Yamasoba, Tatsuya

Abstract

Objectives/Hypothesis: Intracellular entry of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) depends on the interaction between its spike protein with the cellular receptor angiotensin‐converting enzyme 2 (ACE2) and depends on Furin‐mediated spike protein cleavage and spike protein priming by host cell proteases, including transmembrane protease serine 2 (TMPRSS2). As the expression of ACE2, TMPRSS2, and Furin in the middle and inner ear remain unclear, we analyzed the expression of these proteins in mouse ear tissues. Study Design: Animal Research. Methods: We performed immunohistochemical analysis to examine the distribution of ACE2, TMPRSS2, and Furin in the Eustachian tube, middle ear spaces, and cochlea of mice. Results: ACE2 was present in the nucleus of the epithelium of the middle ear and Eustachian tube, as well as in some nuclei of the hair cells in the organ of Corti, in the stria vascularis, and the spiral ganglion cells. ACE2 was also expressed in the cytoplasm of the stria vascularis. TMPRSS2 was expressed in both the nucleus and cytoplasm in the middle spaces, with the expression being stronger in the nucleus in the mucosal epithelium of the middle ear spaces and Eustachian tube. TMPRSS2 was present in the cytoplasm in the organ of Corti and stria vascularis and in the nucleus and cytoplasm in the spiral ganglion. Furin was expressed in the cytoplasm in the middle ear spaces, Eustachian tube, and cochlea. Conclusions: ACE2, TMPRSS2, and Furin are diffusely present in the Eustachian tube, middle ear spaces, and cochlea, suggesting that these tissues are susceptible to SARS‐CoV‐2 infection. Level of Evidence: NA Laryngoscope, 131:E2013–E2017, 2021 [ABSTRACT FROM AUTHOR]

Published
2021
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results