• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国卫生研究院文献>Proceedings of the National Academy of Sciences of the United States of America >PNAS Plus: Output-driven feedback system control platform optimizes combinatorial therapy of tuberculosis using a macrophage cell culture model
【2h】

PNAS Plus: Output-driven feedback system control platform optimizes combinatorial therapy of tuberculosis using a macrophage cell culture model

机译：PNAS Plus：输出驱动的反馈系统控制平台使用巨噬细胞细胞培养模型优化结核病的联合治疗

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务，本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文，但由于OA文献来源多样且变更频繁，仍可能出现获取不到、文献不完整或与标题不符等情况，如果获取不到我们将提供退款服务。请知悉。
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Tuberculosis (TB) remains a major global public health problem, and improved treatments are needed to shorten duration of therapy, decrease disease burden, improve compliance, and combat emergence of drug resistance. Ideally, the most effective regimen would be identified by a systematic and comprehensive combinatorial search of large numbers of TB drugs. However, optimization of regimens by standard methods is challenging, especially as the number of drugs increases, because of the extremely large number of drug–dose combinations requiring testing. Herein, we used an optimization platform, feedback system control (FSC) methodology, to identify improved drug–dose combinations for TB treatment using a fluorescence-based human macrophage cell culture model of TB, in which macrophages are infected with isopropyl β-D-1-thiogalactopyranoside (IPTG)-inducible green fluorescent protein (GFP)-expressing Mycobacterium tuberculosis (Mtb). On the basis of only a single screening test and three iterations, we identified highly efficacious three- and four-drug combinations. To verify the efficacy of these combinations, we further evaluated them using a methodologically independent assay for intramacrophage killing of Mtb; the optimized combinations showed greater efficacy than the current standard TB drug regimen. Surprisingly, all top three- and four-drug optimized regimens included the third-line drug clofazimine, and none included the first-line drugs isoniazid and rifampin, which had insignificant or antagonistic impacts on efficacy. Because top regimens also did not include a fluoroquinolone or aminoglycoside, they are potentially of use for treating many cases of multidrug- and extensively drug-resistant TB. Our study shows the power of an FSC platform to identify promising previously unidentified drug–dose combinations for treatment of TB.
机译：结核病（TB）仍然是全球主要的公共卫生问题，需要改进治疗方法以缩短治疗时间，减轻疾病负担，改善依从性并抵抗耐药性的出现。理想情况下，将通过对大量结核病药物进行系统，全面的组合搜索来确定最有效的治疗方案。但是，通过标准方法优化治疗方案具有挑战性，特别是随着药物数量的增加，因为需要进行大量的药物剂量组合测试。本文中，我们使用优化平台，反馈系统控制（FSC）方法，使用基于荧光的结核病人巨噬细胞细胞培养模型（其中巨噬细胞感染有异丙基β-D- 1-硫代吡喃半乳糖苷（IPTG）诱导表达绿色荧光蛋白（GFP）的结核分枝杆菌（Mtb）。仅基于一次筛选测试和三个迭代，我们确定了高效的三种和四种药物组合。为了验证这些组合的功效，我们使用方法学上独立的方法进一步评估了它们对巨噬细胞内Mtb杀伤的作用；优化组合显示出比当前标准结核病药物治疗方案更高的疗效。出乎意料的是，所有最佳的三药和四药优化方案都包括三线药物氯法齐明，而没有一线药物异烟肼和利福平对疗效无明显或拮抗作用。由于顶级方案也不包含氟喹诺酮或氨基糖苷，因此它们可能可用于治疗许多对多药和广泛耐药结核病的病例。我们的研究表明，FSC平台能够确定以前很有希望的，尚未确定的用于治疗结核病的药物剂量组合。

著录项

相似文献

  • 外文文献
  • 专利
代理获取

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号