摘要翻译：
已知有些微生物会随机地进入和脱离冬眠，而不管环境条件如何[1]。在一个（基因）一致的群体中，一个典型的非常小的亚群变得新陈代谢不活跃，而大多数亚群保持活跃并生长。大肠杆菌、金黄色葡萄球菌(MRSA-超级细菌）、结核分枝杆菌和铜绿假单胞菌[1-3]等细菌表现出持久性。它可以降低细菌在不利环境中的脆弱性[1,4,5]，通过药物有效根除它们更加困难[2,3,6]。在这里，我们表明，药物治疗方案可能必须修改时，考虑持久性，并表征最佳方法，假设总药物剂量是有限的。决定因素是累积毒性、药物根除能力和细菌反应时间。必须使用有针对性的根除战略与持久性有机体作斗争，这些战略表现出两个基本特征。理想情况下，治疗时间应明显长于药物随时间均匀分散而持续的情况；然而，如果必须限制治疗时间，那么药物的应用必须集中在治疗的开始和结束。这些发现偏离了目前的临床实践，因此可能有助于优化和简化治疗。我们使用多目标优化[7]来绘制最优策略，可以推广到其他相关问题。
---
英文标题：
《Optimal strategies for fighting persistent bugs》
---
作者：
Ole Steuernagel, Daniel Polani
---
最新提交年份：
2010
---
分类信息：

一级分类：Quantitative Biology        数量生物学
二级分类：Other Quantitative Biology        其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
--
一级分类：Quantitative Biology        数量生物学
二级分类：Populations and Evolution        种群与进化
分类描述：Population dynamics, spatio-temporal and epidemiological models, dynamic speciation, co-evolution, biodiversity, foodwebs, aging; molecular evolution and phylogeny; directed evolution; origin of life
种群动力学；时空和流行病学模型；动态物种形成；协同进化；生物多样性；食物网；老龄化；分子进化和系统发育；定向进化；生命起源
--

---
英文摘要：
  Some microbial organisms are known to randomly slip into and out of hibernation, irrespective of environmental conditions [1]. In a (genetically) uniform population a typically very small subpopulation becomes metabolically inactive whereas the majority subpopulation remains active and grows. Bacteria such as E. coli, Staphylococcus aureus (MRSA-superbug), Mycobacterium tuberculosis, and Pseudomonas aeruginosa [1-3] show persistence. It can render bacteria less vulnerable in adverse environments [1, 4, 5] and their effective eradication through medication more difficult [2, 3, 6]. Here we show that medication treatment regimes may have to be modified when persistence is taken into account and characterize optimal approaches assuming that the total medication dose is constrained. The determining factors are cumulative toxicity, eradication power of the medication and bacterial response timescales. Persistent organisms have to be fought using tailored eradication strategies which display two fundamental characteristics. Ideally, the treatment time should be significantly longer than in the case of persistence with the medication uniformly spread out over time; however, if treatment time has to be limited, then the application of medication has to be concentrated towards the beginning and end of the treatment. These findings deviate from current clinical practice, and may therefore help to optimize and simplify treatments. Our use of multi-objective optimization [7] to map out the optimal strategies can be generalized to other related problems.
---
PDF链接：
https://arxiv.org/pdf/q-bio/0512003