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Dysferlin缺陷性肌营养不良症:gadofluorine M在小鼠模型MRI的适合性
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作者 s.schmidt A.Vieweger +4 位作者 M.Obst S.Mueller V.Gross M.Gutberlet 陈聪 《国际医学放射学杂志》 2009年第2期176-176,共1页
目的 比较gadofluorine M和Gadomer在7.0T MRI上评估Dysferlin缺陷性肌营养不良症的有效性。方法 实验经当地审查委员会批准通过。患Dysferlin缺陷性肌营养不良症的SJL/J小鼠(n=24)和对照组C57BL/6小鼠(n=24)在12~15周(青年... 目的 比较gadofluorine M和Gadomer在7.0T MRI上评估Dysferlin缺陷性肌营养不良症的有效性。方法 实验经当地审查委员会批准通过。患Dysferlin缺陷性肌营养不良症的SJL/J小鼠(n=24)和对照组C57BL/6小鼠(n=24)在12~15周(青年)或30周(老年)静脉注射动态增强对比剂gadofluorine M 2 μmol或Gadomer 4 μmol,在静注前、中、后行MRI预反转自由稳态进动序列成像。 展开更多
关键词 肌营养不良症 小鼠模型 MRI 缺陷 适合性 C57BL/6小鼠 动态增强 静脉注射
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Search for two-neutrino double-beta decay of^(136)Xe to the 0^(+)_(1)excited state of 136Ba with the complete EXO-200 dataset
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作者 S.Al Kharusi G.Anton +104 位作者 I.Badhrees P.S.Barbeau D.Beck V.Belov T.Bhatta M.Breidenbach T.Brunner G.F.Cao W.R.Cen C.Chambers B.Cleveland M.Coon A.Craycraft T.Daniels L.Darroch S.J.Daugherty J.Davis S.Delaquis A.Der Mesrobian-Kabakian R.DeVoe J.Dilling A.Dolgolenko M.J.Dolinski J.Echevers W.Fairbank Jr. D.Fairbank J.Farine S.Feyzbakhsh P.Fierlinger Y.S.Fu D.Fudenberg P.Gautam R.Gornea G.Gratta C.Hall E.V.Hansen J.Hoessl P.Hufschmidt M.Hughes A.Iverson A.Jamil C.Jessiman M.J.Jewell A.Johnson A.Karelin L.J.Kaufman T.Koffas R.Krücken A.Kuchenkov K.S.Kumar Y.Lan A.Larson B.G.Lenardo D.S.Leonard G.S.Li S.Li Z.Li C.Licciardi Y.H.Lin R.MacLellan T.McElroy T.Michel B.Mong D.C.Moore K.Murray O.Njoya O.Nusair A.Odian I.Ostrovskiy A.Perna A.Piepke A.Pocar F.Retière A.L.Robinson P.C.Rowson J.Runge s.schmidt D.Sinclair K.Skarpaas A.K.Soma V.Stekhanov M.Tarka S.Thibado J.Todd T.Tolba T.I.Totev R.Tsang B.Veenstra V.Veeraraghavan P.Vogel J.-L.Vuilleumier M.Wagenpfeil J.Watkins M.Weber L.J.Wen U.Wichoski G.Wrede S.X.Wu Q.Xia D.R.Yahne L.Yang Y.-R.Yen O.Ya.Zeldovich T.Ziegler 《Chinese Physics C》 SCIE CAS CSCD 2023年第10期1-9,共9页
A new search for two-neutrino double-beta(2νββ)decay of^(136)Xe to the 0+1 excited state of 136Ba is performed with the full EXO-200 dataset.A deep learning-based convolutional neural network is used to discriminat... A new search for two-neutrino double-beta(2νββ)decay of^(136)Xe to the 0+1 excited state of 136Ba is performed with the full EXO-200 dataset.A deep learning-based convolutional neural network is used to discriminate signal from background events.Signal detection efficiency is increased relative to previous searches by EXO-200 by more than a factor of two.With the addition of the Phase II dataset taken with an upgraded detector,the median 90%confidence level half-life sensitivity of 2νββdecay to the 0+1 state of 136Ba is 2.9×10^(24)yr using a total^(136)Xe exposure of 234.1 kg yr.No statistically significant evidence for 2νββdecay to the 0^(+)_(1)state is observed,leading to a lower limit of T2ν1/2(0^(+)→0^(+)_(1))>1.4×10^(24)yr at 90%confidence level,improved by 70%relative to the current world's best constraint. 展开更多
关键词 EXO-200 experiment neutrinoless double beta decay excited state
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