How integration of global omics-data could help preparing for pandemics - a scent of influenza.
How integration of global omics-data could help preparing for pandemics - a scent of influenza.
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DOI：
10.3389/fgene.2014.00080
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发表时间：
2014
影响因子：
3.7
通讯作者：
Schultz MJ
中科院分区：
文献类型：
--
作者：
Bos LD;de Jong MD;Sterk PJ;Schultz MJ
由新出现或重新出现的传染病引起的大流行如果不加以控制，可能导致世界范围内的高死亡率和高发病率。从这个角度来看，我们评估全球组学数据整合的可能性，以便及时为流行病做好准备。这种方法需要两项重大创新。首先，所获得的数据应立即与国际社会分享。简单信号的快速整合的力量以谷歌的TM流感趋势为例，该趋势可以根据在线搜索引擎查询预测流感样疾病的发病率。其次，组学技术需要快速和高通量。我们假设，呼出气的分析将是一个简单，快速和非侵入性的替代方案。呼吸中含有数百种挥发性有机化合物，这些化合物会因感染和炎症而改变。呼吸的分子指纹（呼吸纹）可以使用电子鼻获得，电子鼻依赖于传感器技术。这些呼吸纹可以存储在在线数据库（“呼吸云”）中，并与临床数据相结合。将疑似受试者的呼吸纹与呼吸云进行比较，可以快速确定是否存在病原体。
Pandemics caused by novel emerging or re-emerging infectious diseases could lead to high mortality and morbidity world-wide when left uncontrolled. In this perspective, we evaluate the possibility of integration of global omics-data in order to timely prepare for pandemics. Such an approach requires two major innovations. First, data that is obtained should be shared with the global community instantly. The strength of rapid integration of simple signals is exemplified by Google’sTM Flu Trend, which could predict the incidence of influenza-like illness based on online search engine queries. Second, omics technologies need to be fast and high-throughput. We postulate that analysis of the exhaled breath would be a simple, rapid and non-invasive alternative. Breath contains hundreds of volatile organic compounds that are altered by infection and inflammation. The molecular fingerprint of breath (breathprint) can be obtained using an electronic nose, which relies on sensor technology. These breathprints can be stored in an online database (a “breathcloud”) and coupled to clinical data. Comparison of the breathprint of a suspected subject to the breathcloud allows for a rapid decision on the presence or absence of a pathogen.
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影响因子：
6.7
作者：
Bos LD;Sterk PJ;Schultz MJ
通讯作者：
Schultz MJ
影响因子：
6.7
作者：
Milton, Donald K.;Fabian, M. Patricia;McDevitt, James J.
通讯作者：
McDevitt, James J.
影响因子：
6.1
作者：
Lin, Shuhai;Liu, Ning;Cai, Zongwei
通讯作者：
Cai, Zongwei
DOI：
10.1007/978-1-61779-621-0_4
发表时间：
2012-01-01
期刊：
Methods in molecular biology (Clifton, N.J.)
影响因子：
--
作者：
George, Kirsten St
通讯作者：
George, Kirsten St
影响因子：
64.8
作者：
Jones KE;Patel NG;Levy MA;Storeygard A;Balk D;Gittleman JL;Daszak P
通讯作者：
Daszak P