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生物监测企业用于运行感知,一种基于基因组的追踪病原体毒力的方法。

Biosurveillance enterprise for operational awareness, a genomic-based approach for tracking pathogen virulence.

机构信息

Orion Integrated Biosciences Inc.; New Rochelle, NY USA.

出版信息

Virulence. 2013 Nov 15;4(8):745-51. doi: 10.4161/viru.26893. Epub 2013 Oct 23.

DOI:10.4161/viru.26893
PMID:24152965
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3925708/
Abstract

To protect our civilians and warfighters against both known and unknown pathogens, biodefense stakeholders must be able to foresee possible technological trends that could affect their threat risk assessment. However, significant flaws in how we prioritize our countermeasure-needs continue to limit their development. As recombinant biotechnology becomes increasingly simplified and inexpensive, small groups, and even individuals, can now achieve the design, synthesis, and production of pathogenic organisms for offensive purposes. Under these daunting circumstances, a reliable biosurveillance approach that supports a diversity of users could better provide early warnings about the emergence of new pathogens (both natural and manmade), reverse engineer pathogens carrying traits to avoid available countermeasures, and suggest the most appropriate detection, prophylactic, and therapeutic solutions. While impressive in data mining capabilities, real-time content analysis of social media data misses much of the complexity in the factual reality. Quality issues within freeform user-provided hashtags and biased referencing can significantly undermine our confidence in the information obtained to make critical decisions about the natural vs. intentional emergence of a pathogen. At the same time, errors in pathogen genomic records, the narrow scope of most databases, and the lack of standards and interoperability across different detection and diagnostic devices, continue to restrict the multidimensional biothreat assessment. The fragmentation of our biosurveillance efforts into different approaches has stultified attempts to implement any new foundational enterprise that is more reliable, more realistic and that avoids the scenario of the warning that comes too late. This discussion focus on the development of genomic-based decentralized medical intelligence and laboratory system to track emerging and novel microbial health threats in both military and civilian settings and the use of virulence factors for risk assessment. Examples of the use of motif fingerprints for pathogen discrimination are provided.

摘要

为了保护我们的平民和作战人员免受已知和未知病原体的侵害,生物防御利益相关者必须能够预见可能影响其威胁评估的技术趋势。然而,我们在优先考虑对策需求方面存在重大缺陷,这继续限制了它们的发展。随着重组生物技术变得越来越简单和廉价,现在即使是小团体,甚至是个人,也可以设计、合成和生产用于进攻目的的致病生物体。在这些令人生畏的情况下,一种支持多种用户的可靠生物监测方法可以更好地提供有关新病原体(包括自然和人为)出现的早期预警,对携带可规避现有对策的特征的病原体进行反向工程,并提出最合适的检测、预防和治疗解决方案。虽然在数据挖掘能力方面令人印象深刻,但社交媒体数据的实时内容分析忽略了事实真相中的许多复杂性。免费提供的用户标签中的质量问题和有偏见的引用会极大地削弱我们对信息的信心,从而无法对病原体的自然或人为出现做出关键决策。与此同时,病原体基因组记录中的错误、大多数数据库的范围狭窄以及不同检测和诊断设备之间缺乏标准和互操作性,继续限制了多维生物威胁评估。我们的生物监测工作因不同方法而碎片化,这使得实施任何新的基础企业变得更加困难,这些企业需要更可靠、更现实,并避免出现预警太迟的情况。本讨论重点介绍了基于基因组的去中心化医疗智能和实验室系统的开发,以跟踪军事和民用环境中新兴和新型微生物健康威胁,以及使用毒力因子进行风险评估。提供了用于病原体鉴别特征指纹的示例。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc29/3925708/5548ddc2c733/viru-4-745-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc29/3925708/8aab5a445ee0/viru-4-745-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc29/3925708/5548ddc2c733/viru-4-745-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc29/3925708/8aab5a445ee0/viru-4-745-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc29/3925708/5548ddc2c733/viru-4-745-g2.jpg

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