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821.
822.
Roles of O-acetyl-L-homoserine sulfhydrylases in micro-organisms 总被引:3,自引:0,他引:3
S Yamagata 《Biochimie》1989,71(11-12):1125-1143
O-Acetyl-L-homoserine sulfhydrylase (EC 4.2.99.10) is essential for certain micro-organisms, functioning as a homocysteine synthase in the pathway of methionine synthesis. It participates in an alternative pathway of L-homocysteine synthesis for those microbes in which homocysteine is synthesized mainly via cystathionine. The protein can also catalyze the de novo synthesis of L-cysteine and O-alkyl-L-homoserine in some microorganisms. The enzyme possibly recycles the methylthio group of methionine. 相似文献
823.
Experiments comparing conventional operative treatment and cryosurgery of a murine osteosarcoma showed that local tumor destruction by freezing in situ was similar or superior to amputation concerning survival and formation of metastasis, depending on tumor stage. Limited local resection was less effective. Immune functions affected by cryosurgical tumor destruction included depression of natural killer cell activity and decrease of tumor-specific autologous IgG antibodies in the serum. 相似文献
824.
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826.
Ayumu Yamashita Yuki Sakai Takashi Yamada Noriaki Yahata Akira Kunimatsu Naohiro Okada Takashi Itahashi Ryuichiro Hashimoto Hiroto Mizuta Naho Ichikawa Masahiro Takamura Go Okada Hirotaka Yamagata Kenichiro Harada Koji Matsuo Saori C. Tanaka Mitsuo Kawato Kiyoto Kasai Nobumasa Kato Hidehiko Takahashi Yasumasa Okamoto Okito Yamashita Hiroshi Imamizu 《PLoS biology》2020,18(12)
Many studies have highlighted the difficulty inherent to the clinical application of fundamental neuroscience knowledge based on machine learning techniques. It is difficult to generalize machine learning brain markers to the data acquired from independent imaging sites, mainly due to large site differences in functional magnetic resonance imaging. We address the difficulty of finding a generalizable marker of major depressive disorder (MDD) that would distinguish patients from healthy controls based on resting-state functional connectivity patterns. For the discovery dataset with 713 participants from 4 imaging sites, we removed site differences using our recently developed harmonization method and developed a machine learning MDD classifier. The classifier achieved an approximately 70% generalization accuracy for an independent validation dataset with 521 participants from 5 different imaging sites. The successful generalization to a perfectly independent dataset acquired from multiple imaging sites is novel and ensures scientific reproducibility and clinical applicability.Biomarkers for psychiatric disorders based on neuroimaging data have yet to be put to practical use. This study overcomes the problems of inter-site differences in fMRI data by using a novel harmonization method, thereby successfully constructing a generalizable brain network marker of major depressive disorder across multiple imaging sites. 相似文献
827.
Yutaro Mori Amrendra K. Ajay Jae-Hyung Chang Shan Mou Huiping Zhao Seiji Kishi Jiahua Li Craig R. Brooks Sheng Xiao Heung-Myong Woo Venkata S. Sabbisetti Suetonia C. Palmer Pierre Galichon Li Li Joel M. Henderson Vijay K. Kuchroo Julie Hawkins Takaharu Ichimura Joseph V. Bonventre 《Cell metabolism》2021,33(5):1042-1061.e7