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8篇 您的检索式:作者名="Timothy MO"
    题名 作者 年代 出处 被引量
1Utility of MtCOI polymerase chain reaction-restriction fragment length polymorphism in differentiating between Q and B whitefly Bemisia tabaci biotypes显示文摘侵略,杀虫药剂抵抗, Q 白苍蝇遗传因子型,逐渐地经由植物材料的调停人的运动包括 US 传播了到另外的国家。我们估计了基于 VspI 的 mtCOI 的用途(线粒体细胞色素 oxidase 我) 是的聚合酶链反应限制碎片长度多型性(PCR-RFLP ) 技术为在亚利桑那把 Q 区分开来与主导的 B 遗传因子型的一种快速、划算、可靠的选择。用定序的标准 mtCOI 基因和 mtCOI PCR-RFLP 技术,我们八个白苍蝇五个个人拉紧的 biotyped 各在亚利桑那在不同地点从一品红和棉花收集了。完全的词语索引在二个方法之间被观察,与作为象 B 遗传因子型的 Q 遗传因子型和五件样品被识别的三紧张。我们也在在 GenBank 数据库当前可得到的 B 和 Q 遗传因子型白人苍蝇为 VspI 多型性扫描了 mtCOI 基因序列。这全球屏蔽分别地为 Q 和 B 遗传因子型揭示了三和四种 VspI 多态的类型的存在。不过,所有三个 VspI 多态的 Q 遗传因子型白人苍蝇分享了能被用来把 Q 遗传因子型区分开来与识别的四个 VspI 多态的 B 遗传因子型白人苍蝇的一个普通、唯一的 VspI 地点。这些结果证明基于 VspI 的 mtCOI 基因 PCR-RFLP 为区分白色在 US 并且在其它地方飞的 Q 和 B 遗传因子型提供一个可靠诊断工具。Wei-Hua Ma Xian-Chun Li Timothy J. Dennehy Chao-Liang Lei Mo Wang Benjamin A. Degain Robert L. Nichols 2009Insect Science2009,16,2:5
2Biomechanical analysisof facet and graft loading in a Smith-Robinson type cervical spinemodel显示文摘John MO Timothy AG Michael JS 1994Spine1994,19,16:1
3Hybrid hone implants : self-assembly of peptide amphiphile nanofibers within porous litanium 显示文摘Timothy DS Mustafa OG Scott MO 2008Biomaterials2008,29,2:1
4Shading during the grain filling period increases 2-acetyl-1-pyrroline content in fragrant rice显示文摘Zhaowen Mo Wu Li Shenggang Pan Timothy L Fitzgerald Feng Xiao Yongjian Tang Yilei Wang Meiyang Duan Hua Tian Xiangru Tang 2015Rice2015,,1:1
5The rhizosphere: a playground and battlefield for soilborne pathogens and beneficial microorganisms显示文摘Jos M. Raaijmakers Timothy C. Paulitz Christian Steinberg Claude Alabouvette Yvan Mo?nne-Loccoz 2009Plant and Soil (-)2009,,1:1
6Chronic Arsenic Exposure and Oxidative Stress: OGG! Expression and Arsenic Exposure, Nail Selenium, and Skin Hyperkeratosis in Inner Mongolia 显示文摘Jinyao Mo Yajuan Xia Timothy J Wade 2006Environmental Health Perspectives2006,114,6:1
7Comparative accuracy of the MMPI-2 and the MMPI-A in the diagnosis of psychopathology in 18-years-olds显示文摘Timothy MO Danielle LP 2002Psychological Assessment2002,14,2:1
8A new risk stratification score for patients with suspected cardiac chest pain in emergency departments,based on machine learning显示文摘To the Editor:Chest pain is one of the most common complaints for patients attending emergency departments(EDs)globally.It is important to accurately stratify risk of possible acute coronary syndrome(ACS)for these patients.[1]Several risk stratification scores such as thrombolysis in myocardial infarction(TIMI),global registry for acute coronary events(GRACE),Banach and HEART are helpful.[2]Previous research in our setting compared these four scores and found that the HEART score,with a C-statistic of 0.731,was the best for predicting 7-day major adverse cardiac events(MACE)The purpose of this study was to develop risk stratification prediction models for 7-day MACE in patients with chest pain,utilizing machine learning algorithms such as eXtreme Gradient Boosting(XGBoost),Support Vector Machine(SVM).Hai-Feng Mao Xiao-Hui Chen Yun-Mei Li Si-Yuan Zhang Jun-Rong Mo Min Li Pei-Yi Lin Timothy HRainer Colin AGraham Hui-Lin Jiang 2020Chinese Medical Journal2020,,7:0
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