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5. Quantification of escape from X chromosome inactivation with single-cell omics data reveals heterogeneity across cell types and tissues

Author

Charoensawan, Varodom, Hon, Chung-Chau, Majumder, Partha P., Matangkasombut, Ponpan, Park, Woong-Yang, Prabhakar, Shyam, Shin, Jay W., Carninci, Piero, Chambers, John C., Loh, Marie, Pithukpakorn, Manop, Suktitipat, Bhoom, Yamamoto, Kazuhiko, Rajagopalan, Deepa, Rayan, Nirmala Arul, Sankaran, Shvetha, Chantaraamporn, Juthamard, Chatterjee, Ankita, Ghosh, Supratim, Han, Kyung Yeon, Jevapatarakul, Damita, Nguantad, Sarintip, Sarkar, Sumanta, Thungsatianpun, Narita, Abe, Mai, Furukawa, Seiko, Inoue, Gyo, Myouzen, Keiko, Oh, Jin-Mi, Suzuki, Akari, Ando, Yoshinari, Kojima, Miki, Kouno, Tsukasa, Lim, Jinyeong, Maitra, Arindam, Tan, Le Min, Venkatesh, Prasanna Nori, Choi, Murim, Park, Jong-Eun, Buyamin, Eliora Violain, Kock, Kian Hong, Xuan Lin, Quy Xiao, Moody, Jonathan, Sonthalia, Radhika, Ishigaki, Kazuyoshi, Nakano, Masahiro, Okada, Yukinori, Tomofuji, Yoshihiko, Ho Namkoong, Edahiro, Ryuya, Takano, Tomomi, Nishihara, Hiroshi, Shirai, Yuya, Sonehara, Kyuto, Tanaka, Hiromu, Azekawa, Shuhei, Mikami, Yohei, Lee, Ho, Hasegawa, Takanori, Okudela, Koji, Okuzaki, Daisuke, Motooka, Daisuke, Kanai, Masahiro, Naito, Tatsuhiko, Yamamoto, Kenichi, Wang, Qingbo S., Saiki, Ryunosuke, Ishihara, Rino, Matsubara, Yuta, Hamamoto, Junko, Hayashi, Hiroyuki, Yoshimura, Yukihiro, Tachikawa, Natsuo, Yanagita, Emmy, Hyugaji, Takayoshi, Shimizu, Eigo, Katayama, Kotoe, Kato, Yasuhiro, Morita, Takayoshi, Takahashi, Kazuhisa, Harada, Norihiro, Naito, Toshio, Hiki, Makoto, Matsushita, Yasushi, Takagi, Haruhi, Aoki, Ryousuke, Nakamura, Ai, Harada, Sonoko, Sasano, Hitoshi, Kabata, Hiroki, Masaki, Katsunori, Kamata, Hirofumi, Ikemura, Shinnosuke, Chubachi, Shotaro, Okamori, Satoshi, Terai, Hideki, Morita, Atsuho, Asakura, Takanori, Sasaki, Junichi, Morisaki, Hiroshi, Uwamino, Yoshifumi, Nanki, Kosaku, Uchida, Sho, Uno, Shunsuke, Nishimura, Tomoyasu, Ishiguro, Takashi, Isono, Taisuke, Shibata, Shun, Matsui, Yuma, Hosoda, Chiaki, Takano, Kenji, Nishida, Takashi, Kobayashi, Yoichi, Takaku, Yotaro, Takayanagi, Noboru, Ueda, Soichiro, Tada, Ai, Miyawaki, Masayoshi, Yamamoto, Masaomi, Yoshida, Eriko, Hayashi, Reina, Nagasaka, Tomoki, Arai, Sawako, Kaneko, Yutaro, Sasaki, Kana, Tagaya, Etsuko, Kawana, Masatoshi, Arimura, Ken, Takahashi, Kunihiko, Anzai, Tatsuhiko, Ito, Satoshi, Endo, Akifumi, Uchimura, Yuji, Miyazaki, Yasunari, Honda, Takayuki, Tateishi, Tomoya, Tohda, Shuji, Ichimura, Naoya, Sonobe, Kazunari, Sassa, Chihiro Tani, Nakajima, Jun, Nakano, Yasushi, Nakajima, Yukiko, Anan, Ryusuke, Arai, Ryosuke, Kurihara, Yuko, Harada, Yuko, Nishio, Kazumi, Ueda, Tetsuya, Azuma, Masanori, Saito, Ryuichi, Sado, Toshikatsu, Miyazaki, Yoshimune, Sato, Ryuichi, Haruta, Yuki, Nagasaki, Tadao, Yasui, Yoshinori, Hasegawa, Yoshinori, Mutoh, Yoshikazu, Kimura, Tomoki, Sato, Tomonori, Takei, Reoto, Hagimoto, Satoshi, Noguchi, Yoichiro, Yamano, Yasuhiko, Sasano, Hajime, Ota, Sho, Nakamori, Yasushi, Yoshiya, Kazuhisa, Saito, Fukuki, Yoshihara, Tomoyuki, Wada, Daiki, Iwamura, Hiromu, Kanayama, Syuji, Maruyama, Shuhei, Yoshiyama, Takashi, Ohta, Ken, Kokuto, Hiroyuki, Ogata, Hideo, Tanaka, Yoshiaki, Arakawa, Kenichi, Shimoda, Masafumi, Osawa, Takeshi, Tateno, Hiroki, Hase, Isano, Yoshida, Shuichi, Suzuki, Shoji, Kawada, Miki, Horinouchi, Hirohisa, Saito, Fumitake, Mitamura, Keiko, Hagihara, Masao, Ochi, Junichi, Uchida, Tomoyuki, Baba, Rie, Arai, Daisuke, Ogura, Takayuki, Takahashi, Hidenori, Hagiwara, Shigehiro, Nagao, Genta, Konishi, Shunichiro, Nakachi, Ichiro, Murakami, Koji, Yamada, Mitsuhiro, Sugiura, Hisatoshi, Sano, Hirohito, Matsumoto, Shuichiro, Kimura, Nozomu, Ono, Yoshinao, Baba, Hiroaki, Suzuki, Yusuke, Nakayama, Sohei, Masuzawa, Keita, Namba, Shinichi, Suzuki, Ken, Naito, Yoko, Liu, Yu-Chen, Takuwa, Ayako, Sugihara, Fuminori, Wing, James B., Sakakibara, Shuhei, Hizawa, Nobuyuki, Shiroyama, Takayuki, Miyawaki, Satoru, Kawamura, Yusuke, Nakayama, Akiyoshi, Matsuo, Hirotaka, Yuichi, Maeda, Nii, Takuro, Noda, Yoshimi, Niitsu, Takayuki, Adachi, Yuichi, Enomoto, Takatoshi, Amiya, Saori, Hara, Reina, Yamaguchi, Yuta, Murakami, Teruaki, Kuge, Tomoki, Matsumoto, Kinnosuke, Yamamoto, Yuji, Yamamoto, Makoto, Yoneda, Midori, Kishikawa, Toshihiro, Yamada, Shuhei, Kawabata, Shuhei, Kijima, Noriyuki, Takagaki, Masatoshi, Sasa, Noah, Ueno, Yuya, Suzuki, Motoyuki, Takemoto, Norihiko, Eguchi, Hirotaka, Fukusumi, Takahito, Imai, Takao, Fukushima, Munehisa, Kishima, Haruhiko, Inohara, Hidenori, Tomono, Kazunori, Kato, Kazuto, Takahashi, Meiko, Matsuda, Fumihiko, Hirata, Haruhiko, Takeda, Yoshito, Koh, Hidefumi, Manabe, Tadashi, Funatsu, Yohei, Ito, Fumimaro, Fukui, Takahiro, Shinozuka, Keisuke, Kohashi, Sumiko, Miyazaki, Masatoshi, Shoko, Tomohisa, Kojima, Mitsuaki, Adachi, Tomohiro, Ishikawa, Motonao, Takahashi, Kenichiro, Inoue, Takashi, Hirano, Toshiyuki, Kobayashi, Keigo, Takaoka, Hatsuyo, Watanabe, Kazuyoshi, Miyazawa, Naoki, Kimura, Yasuhiro, Sado, Reiko, Sugimoto, Hideyasu, Kamiya, Akane, Kuwahara, Naota, Fujiwara, Akiko, Matsunaga, Tomohiro, Sato, Yoko, Okada, Takenori, Hirai, Yoshihiro, Kawashima, Hidetoshi, Narita, Atsuya, Niwa, Kazuki, Sekikawa, Yoshiyuki, Nishi, Koichi, Nishitsuji, Masaru, Tani, Mayuko, Suzuki, Junya, Nakatsumi, Hiroki, Ogura, Takashi, Kitamura, Hideya, Hagiwara, Eri, Murohashi, Kota, Okabayashi, Hiroko, Mochimaru, Takao, Nukaga, Shigenari, Satomi, Ryosuke, Oyamada, Yoshitaka, Mori, Nobuaki, Baba, Tomoya, Fukui, Yasutaka, Odate, Mitsuru, Mashimo, Shuko, Makino, Yasushi, Yagi, Kazuma, Hashiguchi, Mizuha, Kagyo, Junko, Shiomi, Tetsuya, Fuke, Satoshi, Saito, Hiroshi, Tsuchida, Tomoya, Fujitani, Shigeki, Takita, Mumon, Morikawa, Daiki, Yoshida, Toru, Izumo, Takehiro, Inomata, Minoru, Kuse, Naoyuki, Awano, Nobuyasu, Tone, Mari, Ito, Akihiro, Nakamura, Yoshihiko, Hoshino, Kota, Maruyama, Junichi, Ishikura, Hiroyasu, Takata, Tohru, Odani, Toshio, Amishima, Masaru, Hattori, Takeshi, Shichinohe, Yasuo, Kagaya, Takashi, Kita, Toshiyuki, Ohta, Kazuhide, Sakagami, Satoru, Koshida, Kiyoshi, Hayashi, Kentaro, Shimizu, Tetsuo, Kozu, Yutaka, Hiranuma, Hisato, Gon, Yasuhiro, Izumi, Namiki, Nagata, Kaoru, Ueda, Ken, Taki, Reiko, Hanada, Satoko, Kawamura, Kodai, Ichikado, Kazuya, Nishiyama, Kenta, Muranaka, Hiroyuki, Nakamura, Kazunori, Hashimoto, Naozumi, Wakahara, Keiko, Koji, Sakamoto, Omote, Norihito, Ando, Akira, Kodama, Nobuhiro, Kaneyama, Yasunari, Shunsuke, Maeda, Kuraki, Takashige, Matsumoto, Takemasa, Yokote, Koutaro, Nakada, Taka-Aki, Abe, Ryuzo, Oshima, Taku, Shimada, Tadanaga, Harada, Masahiro, Takahashi, Takeshi, Ono, Hiroshi, Sakurai, Toshihiro, Shibusawa, Takayuki, Kimizuka, Yoshifumi, Kawana, Akihiko, Sano, Tomoya, Watanabe, Chie, Suematsu, Ryohei, Sageshima, Hisako, Yoshifuji, Ayumi, Ito, Kazuto, Takahashi, Saeko, Ishioka, Kota, Nakamura, Morio, Masuda, Makoto, Wakabayashi, Aya, Watanabe, Hiroki, Ueda, Suguru, Nishikawa, Masanori, Chihara, Yusuke, Takeuchi, Mayumi, Onoi, Keisuke, Shinozuka, Jun, Sueyoshi, Atsushi, Nagasaki, Yoji, Okamoto, Masaki, Ishihara, Sayoko, Shimo, Masatoshi, Tokunaga, Yoshihisa, Kusaka, Yu, Ohba, Takehiko, Isogai, Susumu, Ogawa, Aki, Inoue, Takuya, Fukuyama, Satoru, Eriguchi, Yoshihiro, Yonekawa, Akiko, Kan-o, Keiko, Matsumoto, Koichiro, Kanaoka, Kensuke, Ihara, Shoichi, Komuta, Kiyoshi, Inoue, Yoshiaki, Chiba, Shigeru, Yamagata, Kunihiro, Hiramatsu, Yuji, Kai, Hirayasu, Asano, Koichiro, Oguma, Tsuyoshi, Ito, Yoko, Hashimoto, Satoru, Yamasaki, Masaki, Kasamatsu, Yu, Komase, Yuko, Hida, Naoya, Tsuburai, Takahiro, Oyama, Baku, Takada, Minoru, Kanda, Hidenori, Kitagawa, Yuichiro, Fukuta, Tetsuya, Miyake, Takahito, Yoshida, Shozo, Ogura, Shinji, Abe, Shinji, Kono, Yuta, Togashi, Yuki, Takoi, Hiroyuki, Kikuchi, Ryota, Ogawa, Shinichi, Ogata, Tomouki, Ishihara, Shoichiro, Kanehiro, Arihiko, Ozaki, Shinji, Fuchimoto, Yasuko, Wada, Sae, Fujimoto, Nobukazu, Nishiyama, Kei, Terashima, Mariko, Beppu, Satoru, Yoshida, Kosuke, Narumoto, Osamu, Nagai, Hideaki, Ooshima, Nobuharu, Motegi, Mitsuru, Umeda, Akira, Miyagawa, Kazuya, Shimada, Hisato, Endo, Mayu, Ohira, Yoshiyuki, Watanabe, Masafumi, Inoue, Sumito, Igarashi, Akira, Sato, Masamichi, Sagara, Hironori, Tanaka, Akihiko, Ohta, Shin, Kimura, Tomoyuki, Shibata, Yoko, Tanino, Yoshinori, Nikaido, Takefumi, Minemura, Hiroyuki, Sato, Yuki, Yamada, Yuichiro, Hashino, Takuya, Shinoki, Masato, Iwagoe, Hajime, Takahashi, Hiroshi, Fujii, Kazuhiko, Kishi, Hiroto, Kanai, Masayuki, Imamura, Tomonori, Yamashita, Tatsuya, Yatomi, Masakiyo, Maeno, Toshitaka, Hayashi, Shinichi, Takahashi, Mai, Kuramochi, Mizuki, Kamimaki, Isamu, Tominaga, Yoshiteru, Ishii, Tomoo, Utsugi, Mitsuyoshi, Ono, Akihiro, Tanaka, Toru, Kashiwada, Takeru, Fujita, Kazue, Saito, Yoshinobu, Seike, Masahiro, Watanabe, Hiroko, Matsuse, Hiroto, Kodaka, Norio, Nakano, Chihiro, Oshio, Takeshi, Hirouchi, Takatomo, Makino, Shohei, Egi, Moritoki, Omae, Yosuke, Nannya, Yasuhito, Ueno, Takafumi, Katayama, Kazuhiko, Ai, Masumi, Fukui, Yoshinori, Kumanogoh, Atsushi, Sato, Toshiro, Hasegawa, Naoki, Tokunaga, Katsushi, Ishii, Makoto, Koike, Ryuji, Kitagawa, Yuko, Kimura, Akinori, Imoto, Seiya, Miyano, Satoru, Ogawa, Seishi, Kanai, Takanori, Fukunaga, Koichi, Takeshima, Yusuke, Tanaka, Kentaro, Koichi Matsuda, Yamanashi, Yuji, Furukawa, Yoichi, Morisaki, Takayuki, Murakami, Yoshinori, Kamatani, Yoichiro, Muto, Kaori, Nagai, Akiko, Nakamura, Yusuke, Obara, Wataru, Yamaji, Ken, Asai, Satoshi, Takahashi, Yasuo, Higashiue, Shinichi, Kobayashi, Shuzo, Yamaguchi, Hiroki, Nagata, Yasunobu, Wakita, Satoshi, Nito, Chikako, Iwasaki, Yu-ki, Murayama, Shigeo, Yoshimori, Kozo, Miki, Yoshio, Obata, Daisuke, Higashiyama, Masahiko, Masumoto, Akihide, Koga, Yoshinobu, Koretsune, Yukihiro, Yata, Tomohiro, Ogawa, Kotaro, Namkoong, Ho, Okuno, Tatsusada, Liu, Boxiang, Matsuda, Koichi, and Mochizuki, Hideki

Published
2024
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11. DOCK2 is involved in the host genetics and biology of severe COVID-19

Author

Namkoong, Ho, Edahiro, Ryuya, Takano, Tomomi, Nishihara, Hiroshi, Shirai, Yuya, Sonehara, Kyuto, Tanaka, Hiromu, Azekawa, Shuhei, Mikami, Yohei, Lee, Ho, Hasegawa, Takanori, Okudela, Koji, Okuzaki, Daisuke, Motooka, Daisuke, Kanai, Masahiro, Naito, Tatsuhiko, Yamamoto, Kenichi, Wang, Qingbo S., Saiki, Ryunosuke, Ishihara, Rino, Matsubara, Yuta, Hamamoto, Junko, Hayashi, Hiroyuki, Yoshimura, Yukihiro, Tachikawa, Natsuo, Yanagita, Emmy, Hyugaji, Takayoshi, Shimizu, Eigo, Katayama, Kotoe, Kato, Yasuhiro, Morita, Takayoshi, Takahashi, Kazuhisa, Harada, Norihiro, Naito, Toshio, Hiki, Makoto, Matsushita, Yasushi, Takagi, Haruhi, Aoki, Ryousuke, Nakamura, Ai, Harada, Sonoko, Sasano, Hitoshi, Kabata, Hiroki, Masaki, Katsunori, Kamata, Hirofumi, Ikemura, Shinnosuke, Chubachi, Shotaro, Okamori, Satoshi, Terai, Hideki, Morita, Atsuho, Asakura, Takanori, Sasaki, Junichi, Morisaki, Hiroshi, Uwamino, Yoshifumi, Nanki, Kosaku, Uchida, Sho, Uno, Shunsuke, Nishimura, Tomoyasu, Ishiguro, Takashi, Isono, Taisuke, Shibata, Shun, Matsui, Yuma, Hosoda, Chiaki, Takano, Kenji, Nishida, Takashi, Kobayashi, Yoichi, Takaku, Yotaro, Takayanagi, Noboru, Ueda, Soichiro, Tada, Ai, Miyawaki, Masayoshi, Yamamoto, Masaomi, Yoshida, Eriko, Hayashi, Reina, Nagasaka, Tomoki, Arai, Sawako, Kaneko, Yutaro, Sasaki, Kana, Tagaya, Etsuko, Kawana, Masatoshi, Arimura, Ken, Takahashi, Kunihiko, Anzai, Tatsuhiko, Ito, Satoshi, Endo, Akifumi, Uchimura, Yuji, Miyazaki, Yasunari, Honda, Takayuki, Tateishi, Tomoya, Tohda, Shuji, Ichimura, Naoya, Sonobe, Kazunari, Sassa, Chihiro Tani, Nakajima, Jun, Nakano, Yasushi, Nakajima, Yukiko, Anan, Ryusuke, Arai, Ryosuke, Kurihara, Yuko, Harada, Yuko, Nishio, Kazumi, Ueda, Tetsuya, Azuma, Masanori, Saito, Ryuichi, Sado, Toshikatsu, Miyazaki, Yoshimune, Sato, Ryuichi, Haruta, Yuki, Nagasaki, Tadao, Yasui, Yoshinori, Hasegawa, Yoshinori, Mutoh, Yoshikazu, Kimura, Tomoki, Sato, Tomonori, Takei, Reoto, Hagimoto, Satoshi, Noguchi, Yoichiro, Yamano, Yasuhiko, Sasano, Hajime, Ota, Sho, Nakamori, Yasushi, Yoshiya, Kazuhisa, Saito, Fukuki, Yoshihara, Tomoyuki, Wada, Daiki, Iwamura, Hiromu, Kanayama, Syuji, Maruyama, Shuhei, Yoshiyama, Takashi, Ohta, Ken, Kokuto, Hiroyuki, Ogata, Hideo, Tanaka, Yoshiaki, Arakawa, Kenichi, Shimoda, Masafumi, Osawa, Takeshi, Tateno, Hiroki, Hase, Isano, Yoshida, Shuichi, Suzuki, Shoji, Kawada, Miki, Horinouchi, Hirohisa, Saito, Fumitake, Mitamura, Keiko, Hagihara, Masao, Ochi, Junichi, Uchida, Tomoyuki, Baba, Rie, Arai, Daisuke, Ogura, Takayuki, Takahashi, Hidenori, Hagiwara, Shigehiro, Nagao, Genta, Konishi, Shunichiro, Nakachi, Ichiro, Murakami, Koji, Yamada, Mitsuhiro, Sugiura, Hisatoshi, Sano, Hirohito, Matsumoto, Shuichiro, Kimura, Nozomu, Ono, Yoshinao, Baba, Hiroaki, Suzuki, Yusuke, Nakayama, Sohei, Masuzawa, Keita, Namba, Shinichi, Suzuki, Ken, Naito, Yoko, Liu, Yu-Chen, Takuwa, Ayako, Sugihara, Fuminori, Wing, James B., Sakakibara, Shuhei, Hizawa, Nobuyuki, Shiroyama, Takayuki, Miyawaki, Satoru, Kawamura, Yusuke, Nakayama, Akiyoshi, Matsuo, Hirotaka, Maeda, Yuichi, Nii, Takuro, Noda, Yoshimi, Niitsu, Takayuki, Adachi, Yuichi, Enomoto, Takatoshi, Amiya, Saori, Hara, Reina, Yamaguchi, Yuta, Murakami, Teruaki, Kuge, Tomoki, Matsumoto, Kinnosuke, Yamamoto, Yuji, Yamamoto, Makoto, Yoneda, Midori, Kishikawa, Toshihiro, Yamada, Shuhei, Kawabata, Shuhei, Kijima, Noriyuki, Takagaki, Masatoshi, Sasa, Noah, Ueno, Yuya, Suzuki, Motoyuki, Takemoto, Norihiko, Eguchi, Hirotaka, Fukusumi, Takahito, Imai, Takao, Fukushima, Munehisa, Kishima, Haruhiko, Inohara, Hidenori, Tomono, Kazunori, Kato, Kazuto, Takahashi, Meiko, Matsuda, Fumihiko, Hirata, Haruhiko, Takeda, Yoshito, Koh, Hidefumi, Manabe, Tadashi, Funatsu, Yohei, Ito, Fumimaro, Fukui, Takahiro, Shinozuka, Keisuke, Kohashi, Sumiko, Miyazaki, Masatoshi, Shoko, Tomohisa, Kojima, Mitsuaki, Adachi, Tomohiro, Ishikawa, Motonao, Takahashi, Kenichiro, Inoue, Takashi, Hirano, Toshiyuki, Kobayashi, Keigo, Takaoka, Hatsuyo, Watanabe, Kazuyoshi, Miyazawa, Naoki, Kimura, Yasuhiro, Sado, Reiko, Sugimoto, Hideyasu, Kamiya, Akane, Kuwahara, Naota, Fujiwara, Akiko, Matsunaga, Tomohiro, Sato, Yoko, Okada, Takenori, Hirai, Yoshihiro, Kawashima, Hidetoshi, Narita, Atsuya, Niwa, Kazuki, Sekikawa, Yoshiyuki, Nishi, Koichi, Nishitsuji, Masaru, Tani, Mayuko, Suzuki, Junya, Nakatsumi, Hiroki, Ogura, Takashi, Kitamura, Hideya, Hagiwara, Eri, Murohashi, Kota, Okabayashi, Hiroko, Mochimaru, Takao, Nukaga, Shigenari, Satomi, Ryosuke, Oyamada, Yoshitaka, Mori, Nobuaki, Baba, Tomoya, Fukui, Yasutaka, Odate, Mitsuru, Mashimo, Shuko, Makino, Yasushi, Yagi, Kazuma, Hashiguchi, Mizuha, Kagyo, Junko, Shiomi, Tetsuya, Fuke, Satoshi, Saito, Hiroshi, Tsuchida, Tomoya, Fujitani, Shigeki, Takita, Mumon, Morikawa, Daiki, Yoshida, Toru, Izumo, Takehiro, Inomata, Minoru, Kuse, Naoyuki, Awano, Nobuyasu, Tone, Mari, Ito, Akihiro, Nakamura, Yoshihiko, Hoshino, Kota, Maruyama, Junichi, Ishikura, Hiroyasu, Takata, Tohru, Odani, Toshio, Amishima, Masaru, Hattori, Takeshi, Shichinohe, Yasuo, Kagaya, Takashi, Kita, Toshiyuki, Ohta, Kazuhide, Sakagami, Satoru, Koshida, Kiyoshi, Hayashi, Kentaro, Shimizu, Tetsuo, Kozu, Yutaka, Hiranuma, Hisato, Gon, Yasuhiro, Izumi, Namiki, Nagata, Kaoru, Ueda, Ken, Taki, Reiko, Hanada, Satoko, Kawamura, Kodai, Ichikado, Kazuya, Nishiyama, Kenta, Muranaka, Hiroyuki, Nakamura, Kazunori, Hashimoto, Naozumi, Wakahara, Keiko, Sakamoto, Koji, Omote, Norihito, Ando, Akira, Kodama, Nobuhiro, Kaneyama, Yasunari, Maeda, Shunsuke, Kuraki, Takashige, Matsumoto, Takemasa, Yokote, Koutaro, Nakada, Taka-Aki, Abe, Ryuzo, Oshima, Taku, Shimada, Tadanaga, Harada, Masahiro, Takahashi, Takeshi, Ono, Hiroshi, Sakurai, Toshihiro, Shibusawa, Takayuki, Kimizuka, Yoshifumi, Kawana, Akihiko, Sano, Tomoya, Watanabe, Chie, Suematsu, Ryohei, Sageshima, Hisako, Yoshifuji, Ayumi, Ito, Kazuto, Takahashi, Saeko, Ishioka, Kota, Nakamura, Morio, Masuda, Makoto, Wakabayashi, Aya, Watanabe, Hiroki, Ueda, Suguru, Nishikawa, Masanori, Chihara, Yusuke, Takeuchi, Mayumi, Onoi, Keisuke, Shinozuka, Jun, Sueyoshi, Atsushi, Nagasaki, Yoji, Okamoto, Masaki, Ishihara, Sayoko, Shimo, Masatoshi, Tokunaga, Yoshihisa, Kusaka, Yu, Ohba, Takehiko, Isogai, Susumu, Ogawa, Aki, Inoue, Takuya, Fukuyama, Satoru, Eriguchi, Yoshihiro, Yonekawa, Akiko, Kan-o, Keiko, Matsumoto, Koichiro, Kanaoka, Kensuke, Ihara, Shoichi, Komuta, Kiyoshi, Inoue, Yoshiaki, Chiba, Shigeru, Yamagata, Kunihiro, Hiramatsu, Yuji, Kai, Hirayasu, Asano, Koichiro, Oguma, Tsuyoshi, Ito, Yoko, Hashimoto, Satoru, Yamasaki, Masaki, Kasamatsu, Yu, Komase, Yuko, Hida, Naoya, Tsuburai, Takahiro, Oyama, Baku, Takada, Minoru, Kanda, Hidenori, Kitagawa, Yuichiro, Fukuta, Tetsuya, Miyake, Takahito, Yoshida, Shozo, Ogura, Shinji, Abe, Shinji, Kono, Yuta, Togashi, Yuki, Takoi, Hiroyuki, Kikuchi, Ryota, Ogawa, Shinichi, Ogata, Tomouki, Ishihara, Shoichiro, Kanehiro, Arihiko, Ozaki, Shinji, Fuchimoto, Yasuko, Wada, Sae, Fujimoto, Nobukazu, Nishiyama, Kei, Terashima, Mariko, Beppu, Satoru, Yoshida, Kosuke, Narumoto, Osamu, Nagai, Hideaki, Ooshima, Nobuharu, Motegi, Mitsuru, Umeda, Akira, Miyagawa, Kazuya, Shimada, Hisato, Endo, Mayu, Ohira, Yoshiyuki, Watanabe, Masafumi, Inoue, Sumito, Igarashi, Akira, Sato, Masamichi, Sagara, Hironori, Tanaka, Akihiko, Ohta, Shin, Kimura, Tomoyuki, Shibata, Yoko, Tanino, Yoshinori, Nikaido, Takefumi, Minemura, Hiroyuki, Sato, Yuki, Yamada, Yuichiro, Hashino, Takuya, Shinoki, Masato, Iwagoe, Hajime, Takahashi, Hiroshi, Fujii, Kazuhiko, Kishi, Hiroto, Kanai, Masayuki, Imamura, Tomonori, Yamashita, Tatsuya, Yatomi, Masakiyo, Maeno, Toshitaka, Hayashi, Shinichi, Takahashi, Mai, Kuramochi, Mizuki, Kamimaki, Isamu, Tominaga, Yoshiteru, Ishii, Tomoo, Utsugi, Mitsuyoshi, Ono, Akihiro, Tanaka, Toru, Kashiwada, Takeru, Fujita, Kazue, Saito, Yoshinobu, Seike, Masahiro, Watanabe, Hiroko, Matsuse, Hiroto, Kodaka, Norio, Nakano, Chihiro, Oshio, Takeshi, Hirouchi, Takatomo, Makino, Shohei, Egi, Moritoki, Omae, Yosuke, Nannya, Yasuhito, Ueno, Takafumi, Katayama, Kazuhiko, Ai, Masumi, Fukui, Yoshinori, Kumanogoh, Atsushi, Sato, Toshiro, Hasegawa, Naoki, Tokunaga, Katsushi, Ishii, Makoto, Koike, Ryuji, Kitagawa, Yuko, Kimura, Akinori, Imoto, Seiya, Miyano, Satoru, Ogawa, Seishi, Kanai, Takanori, Fukunaga, Koichi, and Okada, Yukinori

Published
2022
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12. Serum IL-28A/IFN-λ2 is linked to disease severity of COVID-19

Author

Fukuda, Yosuke, Homma, Tetsuya, Inoue, Hideki, Goto, Yuiko, Sato, Yoko, Ikeda, Hitoshi, Onitsuka, Chisato, Sato, Hiroki, Akimoto, Kaho, Ebato, Takaya, Suganuma, Hiromitsu, Kawahara, Tomoko, Mikuni, Hatsuko, Uchida, Yoshitaka, Suzuki, Shintaro, Tanaka, Akihiko, and Sagara, Hironori

Published
2022
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13. The whole blood transcriptional regulation landscape in 465 COVID-19 infected samples from Japan COVID-19 Task Force

Author

Wang, Qingbo S., Edahiro, Ryuya, Namkoong, Ho, Hasegawa, Takanori, Shirai, Yuya, Sonehara, Kyuto, Tanaka, Hiromu, Lee, Ho, Saiki, Ryunosuke, Hyugaji, Takayoshi, Shimizu, Eigo, Katayama, Kotoe, Kanai, Masahiro, Naito, Tatsuhiko, Sasa, Noah, Yamamoto, Kenichi, Kato, Yasuhiro, Morita, Takayoshi, Takahashi, Kazuhisa, Harada, Norihiro, Naito, Toshio, Hiki, Makoto, Matsushita, Yasushi, Takagi, Haruhi, Ichikawa, Masako, Nakamura, Ai, Harada, Sonoko, Sandhu, Yuuki, Kabata, Hiroki, Masaki, Katsunori, Kamata, Hirofumi, Ikemura, Shinnosuke, Chubachi, Shotaro, Okamori, Satoshi, Terai, Hideki, Morita, Atsuho, Asakura, Takanori, Sasaki, Junichi, Morisaki, Hiroshi, Uwamino, Yoshifumi, Nanki, Kosaku, Uchida, Sho, Uno, Shunsuke, Nishimura, Tomoyasu, Ishiguro, Takashri, Isono, Taisuke, Shibata, Shun, Matsui, Yuma, Hosoda, Chiaki, Takano, Kenji, Nishida, Takashi, Kobayashi, Yoichi, Takaku, Yotaro, Takayanagi, Noboru, Ueda, Soichiro, Tada, Ai, Miyawaki, Masayoshi, Yamamoto, Masaomi, Yoshida, Eriko, Hayashi, Reina, Nagasaka, Tomoki, Arai, Sawako, Kaneko, Yutaro, Sasaki, Kana, Tagaya, Etsuko, Kawana, Masatoshi, Arimura, Ken, Takahashi, Kunihiko, Anzai, Tatsuhiko, Ito, Satoshi, Endo, Akifumi, Uchimura, Yuji, Miyazaki, Yasunari, Honda, Takayuki, Tateishi, Tomoya, Tohda, Shuji, Ichimura, Naoya, Sonobe, Kazunari, Sassa, Chihiro Tani, Nakajima, Jun, Nakano, Yasushi, Nakajima, Yukiko, Anan, Ryusuke, Arai, Ryosuke, Kurihara, Yuko, Harada, Yuko, Nishio, Kazumi, Ueda, Tetsuya, Azuma, Masanori, Saito, Ryuichi, Sado, Toshikatsu, Miyazaki, Yoshimune, Sato, Ryuichi, Haruta, Yuki, Nagasaki, Tadao, Yasui, Yoshinori, Hasegawa, Yoshinori, Mutoh, Yoshikazu, Kimura, Tomoki, Sato, Tomonori, Takei, Reoto, Hagimoto, Satoshi, Noguchi, Yoichiro, Yamano, Yasuhiko, Sasano, Hajime, Ota, Sho, Nakamori, Yasushi, Yoshiya, Kazuhisa, Saito, Fukuki, Yoshihara, Tomoyuki, Wada, Daiki, Iwamura, Hiromu, Kanayama, Syuji, Maruyama, Shuhei, Yoshiyama, Takashi, Ohta, Ken, Kokuto, Hiroyuki, Ogata, Hideo, Tanaka, Yoshiaki, Arakawa, Kenichi, Shimoda, Masafumi, Osawa, Takeshi, Tateno, Hiroki, Hase, Isano, Yoshida, Shuichi, Suzuki, Shoji, Kawada, Miki, Horinouchi, Hirohisa, Saito, Fumitake, Mitamura, Keiko, Hagihara, Masao, Ochi, Junichi, Uchida, Tomoyuki, Baba, Rie, Arai, Daisuke, Ogura, Takayuki, Takahashi, Hidenori, Hagiwara, Shigehiro, Nagao, Genta, Konishi, Shunichiro, Nakachi, Ichiro, Murakami, Koji, Yamada, Mitsuhiro, Sugiura, Hisatoshi, Sano, Hirohito, Matsumoto, Shuichiro, Kimura, Nozomu, Ono, Yoshinao, Baba, Hiroaki, Suzuki, Yusuke, Nakayama, Sohei, Masuzawa, Keita, Namba, Shinichi, Shiroyama, Takayuki, Noda, Yoshimi, Niitsu, Takayuki, Adachi, Yuichi, Enomoto, Takatoshi, Amiya, Saori, Hara, Reina, Yamaguchi, Yuta, Murakami, Teruaki, Kuge, Tomoki, Matsumoto, Kinnosuke, Yamamoto, Yuji, Yamamoto, Makoto, Yoneda, Midori, Tomono, Kazunori, Kato, Kazuto, Hirata, Haruhiko, Takeda, Yoshito, Koh, Hidefumi, Manabe, Tadashi, Funatsu, Yohei, Ito, Fumimaro, Fukui, Takahiro, Shinozuka, Keisuke, Kohashi, Sumiko, Miyazaki, Masatoshi, Shoko, Tomohisa, Kojima, Mitsuaki, Adachi, Tomohiro, Ishikawa, Motonao, Takahashi, Kenichiro, Inoue, Takashi, Hirano, Toshiyuki, Kobayashi, Keigo, Takaoka, Hatsuyo, Watanabe, Kazuyoshi, Miyazawa, Naoki, Kimura, Yasuhiro, Sado, Reiko, Sugimoto, Hideyasu, Kamiya, Akane, Kuwahara, Naota, Fujiwara, Akiko, Matsunaga, Tomohiro, Sato, Yoko, Okada, Takenori, Hirai, Yoshihiro, Kawashima, Hidetoshi, Narita, Atsuya, Niwa, Kazuki, Sekikawa, Yoshiyuki, Nishi, Koichi, Nishitsuji, Masaru, Tani, Mayuko, Suzuki, Junya, Nakatsumi, Hiroki, Ogura, Takashi, Kitamura, Hideya, Hagiwara, Eri, Murohashi, Kota, Okabayashi, Hiroko, Mochimaru, Takao, Nukaga, Shigenari, Satomi, Ryosuke, Oyamada, Yoshitaka, Mori, Nobuaki, Baba, Tomoya, Fukui, Yasutaka, Odate, Mitsuru, Mashimo, Shuko, Makino, Yasushi, Yagi, Kazuma, Hashiguchi, Mizuha, Kagyo, Junko, Shiomi, Tetsuya, Fuke, Satoshi, Saito, Hiroshi, Tsuchida, Tomoya, Fujitani, Shigeki, Takita, Mumon, Morikawa, Daiki, Yoshida, Toru, Izumo, Takehiro, Inomata, Minoru, Kuse, Naoyuki, Awano, Nobuyasu, Tone, Mari, Ito, Akihiro, Nakamura, Yoshihiko, Hoshino, Kota, Maruyama, Junichi, Ishikura, Hiroyasu, Takata, Tohru, Odani, Toshio, Amishima, Masaru, Hattori, Takeshi, Shichinohe, Yasuo, Kagaya, Takashi, Kita, Toshiyuki, Ohta, Kazuhide, Sakagami, Satoru, Koshida, Kiyoshi, Hayashi, Kentaro, Shimizu, Tetsuo, Kozu, Yutaka, Hiranuma, Hisato, Gon, Yasuhiro, Izumi, Namiki, Nagata, Kaoru, Ueda, Ken, Taki, Reiko, Hanada, Satoko, Kawamura, Kodai, Ichikado, Kazuya, Nishiyama, Kenta, Muranaka, Hiroyuki, Nakamura, Kazunori, Hashimoto, Naozumi, Wakahara, Keiko, Koji, Sakamoto, Omote, Norihito, Ando, Akira, Kodama, Nobuhiro, Kaneyama, Yasunari, Maeda, Shunsuke, Kuraki, Takashige, Matsumoto, Takemasa, Yokote, Koutaro, Nakada, Taka-Aki, Abe, Ryuzo, Oshima, Taku, Shimada, Tadanaga, Harada, Masahiro, Takahashi, Takeshi, Ono, Hiroshi, Sakurai, Toshihiro, Shibusawa, Takayuki, Kimizuka, Yoshifumi, Kawana, Akihiko, Sano, Tomoya, Watanabe, Chie, Suematsu, Ryohei, Sageshima, Hisako, Yoshifuji, Ayumi, Ito, Kazuto, Takahashi, Saeko, Ishioka, Kota, Nakamura, Morio, Masuda, Makoto, Wakabayashi, Aya, Watanabe, Hiroki, Ueda, Suguru, Nishikawa, Masanori, Chihara, Yusuke, Takeuchi, Mayumi, Onoi, Keisuke, Shinozuka, Jun, Sueyoshi, Atsushi, Nagasaki, Yoji, Okamoto, Masaki, Ishihara, Sayoko, Shimo, Masatoshi, Tokunaga, Yoshihisa, Kusaka, Yu, Ohba, Takehiko, Isogai, Susumu, Ogawa, Aki, Inoue, Takuya, Fukuyama, Satoru, Eriguchi, Yoshihiro, Yonekawa, Akiko, Kan-o, Keiko, Matsumoto, Koichiro, Kanaoka, Kensuke, Ihara, Shoichi, Komuta, Kiyoshi, Inoue, Yoshiaki, Chiba, Shigeru, Yamagata, Kunihiro, Hiramatsu, Yuji, Kai, Hirayasu, Asano, Koichiro, Oguma, Tsuyoshi, Ito, Yoko, Hashimoto, Satoru, Yamasaki, Masaki, Kasamatsu, Yu, Komase, Yuko, Hida, Naoya, Tsuburai, Takahiro, Oyama, Baku, Takada, Minoru, Kanda, Hidenori, Kitagawa, Yuichiro, Fukuta, Tetsuya, Miyake, Takahito, Yoshida, Shozo, Ogura, Shinji, Abe, Shinji, Kono, Yuta, Togashi, Yuki, Takoi, Hiroyuki, Kikuchi, Ryota, Ogawa, Shinichi, Ogata, Tomouki, Ishihara, Shoichiro, Kanehiro, Arihiko, Ozaki, Shinji, Fuchimoto, Yasuko, Wada, Sae, Fujimoto, Nobukazu, Nishiyama, Kei, Terashima, Mariko, Beppu, Satoru, Yoshida, Kosuke, Narumoto, Osamu, Nagai, Hideaki, Ooshima, Nobuharu, Motegi, Mitsuru, Umeda, Akira, Miyagawa, Kazuya, Shimada, Hisato, Endo, Mayu, Ohira, Yoshiyuki, Watanabe, Masafumi, Inoue, Sumito, Igarashi, Akira, Sato, Masamichi, Sagara, Hironori, Tanaka, Akihiko, Ohta, Shin, Kimura, Tomoyuki, Shibata, Yoko, Tanino, Yoshinori, Nikaido, Takefumi, Minemura, Hiroyuki, Sato, Yuki, Yamada, Yuichiro, Hashino, Takuya, Shinoki, Masato, Iwagoe, Hajime, Takahashi, Hiroshi, Fujii, Kazuhiko, Kishi, Hiroto, Kanai, Masayuki, Imamura, Tomonori, Yamashita, Tatsuya, Yatomi, Masakiyo, Maeno, Toshitaka, Hayashi, Shinichi, Takahashi, Mai, Kuramochi, Mizuki, Kamimaki, Isamu, Tominaga, Yoshiteru, Ishii, Tomoo, Utsugi, Mitsuyoshi, Ono, Akihiro, Tanaka, Toru, Kashiwada, Takeru, Fujita, Kazue, Saito, Yoshinobu, Seike, Masahiro, Watanabe, Hiroko, Matsuse, Hiroto, Kodaka, Norio, Nakano, Chihiro, Oshio, Takeshi, Hirouchi, Takatomo, Makino, Shohei, Egi, Moritoki, Omae, Yosuke, Nannya, Yasuhito, Ueno, Takafumi, Takano, Tomomi, Katayama, Kazuhiko, Ai, Masumi, Kumanogoh, Atsushi, Sato, Toshiro, Hasegawa, Naoki, Tokunaga, Katsushi, Ishii, Makoto, Koike, Ryuji, Kitagawa, Yuko, Kimura, Akinori, Imoto, Seiya, Miyano, Satoru, Ogawa, Seishi, Kanai, Takanori, Fukunaga, Koichi, and Okada, Yukinori

Published
2022
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14. Nationwide survey of refractory asthma with bronchiectasis by inflammatory subtypes

Author

Nomura, Natsuko, Matsumoto, Hisako, Yokoyama, Akihito, Nishimura, Yoshihiro, Asano, Koichiro, Niimi, Akio, Tohda, Yuji, Harada, Norihiro, Nagase, Hiroyuki, Nagata, Makoto, Inoue, Hiromasa, Kondo, Mitsuko, Horiguchi, Takahiko, Miyahara, Nobuaki, Hizawa, Nobuyuki, Hojo, Masayuki, Hattori, Noboru, Hashimoto, Naozumi, Yamasaki, Akira, Kadowaki, Toru, Kimura, Tomoki, Miki, Mari, Taniguchi, Hirokazu, Toyoshima, Mikio, Kawamura, Tetsuji, Matsuno, Osamu, Sato, Yoko, Sunadome, Hironobu, Nagasaki, Tadao, Oguma, Tsuyoshi, and Hirai, Toyohiro

Published
2022
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17. Comparison between the sodium chloride content and labeled salt value of industrially prepared Japanese single dishes.

Author

Sato, Yoko, Suzuki, Kumiko, and Inagaki, Runa

Subjects
*SODIUM content of food, *DECISION making, *DECISION trees, *CHINESE cooking, *FOOD labeling
Abstract

Salt intake reduction is a global concern. In particular, Japanese consume higher amounts of salt than those of other ethnicities. The sodium content is mentioned on the label of industrially prepared dishes with an intention of reducing salt intake. This study aimed to evaluate the difference between the actual sodium content and labeled salt value of industrially prepared Japanese single dishes. Samples labeled "estimated" were collected and classified as Japanese, Western, and Chinese cuisines. The sodium content ranged from 180 to 1011 mg/100 g. The sodium content was higher than their reported values in other countries. Specifically, Chinese dishes contained high amounts of sodium, although the chloride content was similar across cuisine styles. Further, the molar ratio (i.e., sodium/chloride) had no significant effect on the difference between the actual content and labeled value. The measured salt contents were 20% higher than the labeled values. The results of decision tree analysis indicated that if the labeled salt value of stir‐fried foods is determined by calculation, the actual sodium content is much higher than the labeled salt value. These findings are crucial for customers, dietitian, and researchers as they refer to the labeled salt value to determine the sodium content of industrially prepared foods. [ABSTRACT FROM AUTHOR]

Published
2024
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24. Heat Shock Related Protein Expression in Abdominal Testes of Asian Elephant (Elephas maximus).

Author

Sato, Yoko, Tharasanit, Theerawat, Thitaram, Chatchote, Somgird, Chaleamchat, Mahasawangkul, Sittidet, Thongtip, Nikorn, Chatdarong, Kaywalee, Tiptanavattana, Narong, Taniguchi, Masayasu, Otoi, Takeshige, and Techakumphu, Mongkol

Subjects
*PROLIFERATING cell nuclear antigen, *HEAT shock factors, *ASIATIC elephant, *HEAT shock proteins, *SPERMATOGENESIS
Abstract

Simple Summary: In the abdominal testes of most mammals, with the exception of elephants and a few animal species, spermatogenesis is characterised by an arrest of spermatogenesis due to heat stress. However, the mechanisms underlying normal spermatogenesis in the elephant abdominal testis remain unknown. We hypothesised that comparing the expression of heat stress tolerance molecules of elephant testes with that of other animals and investigating the mechanism of spermatogenesis in elephants might provide clues to overcome the causes of heat stress-induced spermatogenesis dysfunction. The results showed that the elephant's body cells, other than the testes, have a similar mechanism to those of other mammals but that the spermatogenic cells have a different mechanism, with different molecular immunoexpression under heat stress in the abdomen. These findings suggest that these molecules and their relationships may be important in future investigations of the mechanisms that overcome heat stress to maintain spermatogenesis in elephants. The abdominal testes of Asian elephants show normal spermatogenesis. Heat shock in cryptorchid testes elevates heat shock factor (HSF) expression, leading to germ cell apoptosis, while increased heat shock proteins (HSPs) levels provide protection. To investigate how heat shock affects elephant spermatogenic cells, focusing on heat shock-related molecules and the cell death mechanism, immunohistochemistry and TUNEL staining were employed to assess the immunoexpression of several heat shock-related molecules and the status of apoptosis in elephant fibroblasts (EF) induced by heat shock stimulus. Additionally, the immunoexpression of heat shock-related molecules and cell proliferation status in the elephant spermatogenic cells. Our finding indicated that heat shock-induced HSF1 immunoexpression in EF leads to apoptosis mediated by T-cell death-associated gene 51 (TDAG51) while also upregulating HSP70 to protect damaged cells. In elephant spermatogenic cells, immunostaining revealed a predominance of proliferating cell nuclear antigen (PCNA)-positive cells with minimal TDAG51- and TUNEL-positive cells, suggesting active proliferation and apoptosis suppression during normal spermatogenesis in the abdominal testis. Interestingly, spermatogonia co-immunoexpressed HSF1 and HSP90, potentially reducing apoptosis through protective mechanisms different from those observed in other mammals. Spermatogenic cells did not show immunolocalisation of HSP70, and hence, it may not contribute to protecting the spermatogonia from heat shock because the transcriptional activity of HSF1 is suppressed by HSP90A binding. This study provides insight into the specific heat shock response and defence mechanisms in elephant spermatogenic cells and may contribute to our understanding of species-specific adaptation to environmental stresses of the testis. [ABSTRACT FROM AUTHOR]

Published
2024
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30. Effectiveness of a 23-valent pneumococcal polysaccharide vaccine for the prevention of pneumococcal pneumonia in the elderly with chronic respiratory diseases: a case–control study of a single center

Author

Masuda, Toshihiro, Nakatani, Eiji, Shirai, Toshihiro, Akamatsu, Taisuke, Tamura, Kanami, Takahashi, Shingo, Tanaka, Yuko, Watanabe, Hirofumi, Endo, Yoshinari, Suzuki, Takahito, Saigusa, Mika, Yamamoto, Akito, Morita, Satoru, Sato, Yoko, and Asada, Kazuhiro

Published
2021
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32. Psychometric Properties of the Spence Children's Anxiety Scale with Adolescents in Japanese High Schools

Author

Ishikawa, Shin-ichi, Takeno, Yayoi, Sato, Yoko, Kishida, Kohei, Yatagai, Yuto, and Spence, Susan H.

Abstract

This study investigated anxiety symptoms of Japanese adolescents in community high schools. Japanese high school students (N = 1500) from diverse types of schools including general, vocational, and part-time schools completed the Spence Children's Anxiety Scale (SCAS). First, confirmatory factor analysis supported the 6-factor structure with strong goodness-of-fit indices comparable with the original studies as well as those with Japanese elementary and junior high school students. Girls showed more anxiety symptoms, and items related to worry, insects/spiders phobia, checking, and fear of negative evaluations were the most common symptoms, similar to younger youth. Finally, students who attended part-time high school reported higher anxiety symptoms than those in full-time schools. The utility of the SCAS for assessment of anxiety symptoms in high school students and the need for preventive interventions for students at risk for developing anxiety were discussed.

Published
2018
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34. Retrospective analysis for predictors of postsurgical complications from third molar extraction with use of oxytetracycline–hydrocortisone‐coated gauze inserted in extraction socket.

Author

Matsuda, Sayumi, Sato, Yoko, Otake, Hiroki, Takei, Shingo, Nakamura, Arihiro, Fukuta, Kohta, Abe, Atsushi, and Adachi, Moriyasu

Abstract

Aim: Our previous study proposed a technique of inserting gauze coated with oxytetracycline–hydrocortisone ointment into the extraction socket that suppressed the occurrence of dry socket and post‐extraction pain compared with the gauze‐free group. In this study, we estimated the incidence of dry socket and post‐extraction infection in patients with ointment gauze insertion and identified predictors of post‐extraction pain and change in maximum opening volume. Methods: This retrospective study was carried out on patients who underwent lower third molar extraction in the Department of Oral Surgery at a general hospital in Japan. Results: The incidence of dry socket and infection after tooth extraction was 1.05% and 0.35%. The mean visual analog scale (VAS) on the operative day was 4.15; the VAS for postoperative day (POD)1 and POD7 were 2.28 and 0.55, respectively. The percentage change in maximum mouth opening on POD1 was −9.88%, and that on POD7 was −1.51%. Multivariable analysis indicated that age and Winter position classification were predictors of POD1 VAS, and female sex, smoking, and Winter position classification were predictors of POD7 VAS. Winter position classification and preoperative maximum mouth opening, respectively, were identified as predictors of maximum mouth opening percent change on POD1 and POD7. Conclusions: The insertion of gauze coated with oxytetracycline–hydrocortisone ointment into the extraction socket of the mandibular third molar showed a low incidence of dry socket and post‐extraction infection. Moreover, the Winter position classification was suggested to be an independent predictor of postoperative pain and the maximum mouth opening percent change. [ABSTRACT FROM AUTHOR]

Published
2024
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37. Oral communication problems and strategies of Japanese university EFL learners : a descriptive study using retrospective verbal reports

Author

Sato, Yoko

Subjects
428.24956
Abstract

This study investigates the oral communication problems and strategies of Japanese university EFL learners, using the retrospective verbal report technique. Thirty-two students, roughly at an intermediate level of English proficiency, participated in the study. Interaction data were elicited through video-recorded one-to-one face-to-face coral proficiency interviews, each between a learner and a NS interlocutor-assessor. The video-recording was then used as a prompt in the subsequent retrospective verbal report sessions, in which the participants verbalised their mental experiences about communication problems and strategies during the interaction.

Published
2008

42. Computational fluid dynamics analysis of the effects of total weight and food on the water temperature distribution and flow in a pot during cooking.

Author

Arata, Risa, Nagata, Yusaku, and Sato, Yoko

Subjects
WATER temperature, TEMPERATURE distribution, WATER distribution, ROOT crops, FINITE element method, COMPUTATIONAL fluid dynamics, FLOW velocity
Abstract

Uniform quality of cooked foods regardless of its position in the pot is desirable. However, there are no research about the effect of cooking scale on the flow and water temperature distribution. This study investigated the effects of the weight and the presence of food on the water temperature distribution and flow during cooking. Using nylon cylinders with thermophysical properties similar to those of root vegetables, the water temperature near the inner surface of the pot was measured. The water temperature and flow were simulated with 2D models based on the finite element method. The water temperature was highly uniform at a total weight of 20 kg than at 3 kg due to the greater convection and faster flow velocity. The water flow velocity was lower with nylon cylinders than in its absence and decreases with decreasing sample size. This study demonstrates the usefulness of combining simulations with nylon cylinders. Practical applications: The evaluation of temperature distribution and water flow during cooking is important for ensuring uniform quality of products in a pot. Particularly, it is important to evaluate the effect of cooking scale, presence of food and ingredient size. However, the experimental verification of large‐scale cooking is costly and time‐consuming. This study shows the usefulness of combining computational fluid dynamics (CFD) simulation with the nylon cylinders having thermophysical properties similar to those of root vegetables as food analogs. The CFD analysis revealed that increasing cooking scale increases the water flow velocity and uniformity of water temperature. This result should be considered in the actual large‐scale cooking of prototypes, which are tested at small scale, for example, in laboratories. Furthermore, small‐sized foods hinder the flow and cause uneven water temperature distribution. The findings suggest that sample size affects the temperature and uniformity in quality of cooked products in a pot. [ABSTRACT FROM AUTHOR]

Published
2023
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43. KEGG tools for classification and analysis of viral proteins.

Author

Jin, Zhao, Sato, Yoko, Kawashima, Masayuki, and Kanehisa, Minoru

Abstract

The KEGG database and analysis tools (https://www.kegg.jp) have been developed mostly for understanding genes and genomes of cellular organisms. The KO (KEGG Orthology) dataset, which is a collection of functional orthologs, plays the role of linking genes in the genome to pathways and other molecular networks, enabling KEGG mapping to uncover hidden features in the genome. Although viruses were part of KEGG for some time, they were not fully integrated in the KEGG analysis tools, because the KO assignment rate is very low for virus genes. To supplement KOs a new dataset named virus ortholog clusters (VOCs) is computationally generated, covering 90% of viral proteins in KEGG. VOCs can be used, in place of KOs, for taxonomy mapping to uncover relationships of sequence similarity groups and taxonomic groups and for identifying conserved gene orders in virus genomes. Furthermore, selected VOCs are used to define tentative KOs for characterizing protein functions. Here an overview of KEGG tools is presented focusing on these extensions for viral protein analysis. [ABSTRACT FROM AUTHOR]

Published
2023
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44. Natto extract inhibits infection caused by the Aujeszky's disease virus in mice.

Author

Kobayashi, Junya, Wen, Rongduo, Nishikawa, Takanobu, Nunomura, Yuka, Suzuki, Takehito, Sejima, Yudai, Gokan, Toshiya, Furukawa, Makio, Yokota, Tomoko, Osawa, Nanako, Sato, Yoko, Nibu, Yutaka, Mizutani, Tetsuya, and Oba, Mami

Subjects
AUJESZKY'S disease virus, INTERFERON receptors
Abstract

Aujeszky's disease virus (ADV), also known as Suid alphaherpesvirus 1, which mainly infects swine, causes life‐threatening neurological disorders. This disease is a serious global risk factor for economic losses in the swine industry. The development of new anti‐ADV drugs is highly anticipated and required. Natto, a traditional Japanese fermented food made from soybeans, is a well‐known health food. In our previous study, we confirmed that natto has the potential to inhibit viral infections by severe acute respiratory syndrome coronavirus 2 and bovine alphaherpesvirus 1 through their putative serine protease(s). In this study, we found that an agent(s) in natto functionally impaired ADV infection in cell culture assays. In addition, ADV treated with natto extract lost viral infectivity in the mice. We conducted an HPLC gel‐filtration analysis of natto extract and molecular weight markers and confirmed that Fraction No. 10 had ADV‐inactivating ability. Furthermore, the antiviral activity of Fraction No. 10 was inhibited by the serine protease inhibitor 4‐(2‐Aminoethyl) benzene sulfonyl fluoride hydrochloride (AEBSF). These results also suggest that Fraction No. 10, adjacent to the 12.5 kDa peak of the marker in natto extract, may inactivate ADV by proteolysis. Our findings provide new avenues of research for the prevention of Aujeszky's disease. [ABSTRACT FROM AUTHOR]

Published
2023
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49. Association of Eicosapentaenoic and Docosahexaenoic Acid Intake with Low Birth Weight in the Second Trimester: The Japan Pregnancy Eating and Activity Cohort Study.

Author

Yoshimura, Momoka, Fujita, Megumi, Shibata, Ai, Ohori, Riko, Aoyama, Satoko, Yonezawa, Kaori, Sato, Yoko, Sasaki, Satoshi, Matsuzaki, Masayo, Suetsugu, Yoshiko, and Haruna, Megumi

Abstract

This study examined the association of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) intake during the second trimester with low birth weight (LBW) in pregnant Japanese women and was conducted in conjunction with the Japan Pregnancy Eating and Activity Cohort (J-PEACH) study. The study included 504 pregnant women from four Japanese sites. During the second trimester (14–27 weeks), the participants filled out a self-administered questionnaire assessing the frequency of DHA and EPA supplement intake in the past month, as well as a brief-type self-administered diet history questionnaire (BDHQ). The analysis involved data from two time points: responses to the BDHQ and infant data at birth. In total, 471 and 33 participants were classified into the normal birth weight and LBW groups, respectively. The participants were divided into high-, medium-, and low-intake groups based on their total dietary and EPA and DHA supplementary intakes. The Cochran–Armitage trend test was used to analyze the data; the prevalence of LBW was higher in the low-intake group (p = 0.04). There was no significant sex-based trend (p = 0.27 and p = 0.35). In Japanese women, low dietary and supplementary EPA and DHA intake until the second trimester were risk factors for LBW. [ABSTRACT FROM AUTHOR]

Published
2023
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50. Longitudinal analysis of long-term outcomes of colorectal cancer after laparotomy and laparoscopic surgery: The Shizuoka study.

Author

Kojimahara, Noriko, Sato, Yasuto, Sato, Yoko, Kojimahara, Fumihiro, Takahashi, Katsuyuki, and Nakatani, Eiji

Subjects
LAPAROSCOPIC surgery, COLORECTAL cancer, ENDOSCOPIC surgery, CANCER prognosis, ABDOMINAL surgery
Abstract

Background: Long-term cancer prognosis after initial surgical procedures is an unlikely endpoint for clinical trials. Medical claim databases may aid in addressing this issue regardless of limited information on disease and patient background. However, the long-term prognosis (especially regarding long-term care needs) following surgical procedures remains unclear. This study aimed to assess whether long-term outcomes, such as the exacerbation of long-term care needs and mortality, differ with surgical methods. Methods: Using a longitudinal study with linkage between medical claim and long-term care database, patients with primary colorectal cancer who underwent initial colonoscopies were identified through anonymized data in Japan (Shizuoka Kokuho Database, 2012–2018). Odds ratios (ORs) for long-term outcomes (long-term care needs and all-cause mortality during a 6.5-year follow-up period) were analyzed using logistic regression to compare laparoscopy and endoscopic surgery to laparotomy. Results: Overall, 3,744 primary colorectal cancer cases (822 laparotomies, 705 laparoscopies, and 2,217 endoscopic surgeries) were included. Compared to the laparotomy group, the crude OR for exacerbation of long-term care needs in the laparoscopic surgery group was 0.376 (95% confidence interval, 0.227, 0.624), while the OR for all-cause mortality was 0.22 (0.329, 0.532). Conclusion: This is the first study to analyze long-term prognosis after surgery for patients with colorectal cancer to combine medical and long-term needs data. As the national health insurance claim database rarely includes information on cancer stage and comorbidities, better prognosis on endoscopic surgery may need careful interpretation. Therefore, laparoscopy has superior outcomes in terms of long-term care needs and mortality compared to those of laparotomy. [ABSTRACT FROM AUTHOR]

Published
2023
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