Analysis of stochastic fluctuations in responsiveness is a critical step toward personalized anesthesia

被引:28
作者
McKinstry-Wu, Andrew R. [1 ]
Wasilczuk, Andrzej Z. [1 ,2 ]
Harrison, Benjamin A. [1 ]
Bedell, Victoria M. [1 ]
Sridharan, Mathangi J. [3 ]
Breig, Jayce J. [4 ]
Pack, Michael [5 ]
Kelz, Max B. [1 ,2 ]
Proekt, Alexander [1 ]
机构
[1] Univ Penn, Dept Anesthesiol & Crit Care, Philadelphia, PA 19104 USA
[2] Univ Penn, Dept Bioengn, Philadelphia, PA 19104 USA
[3] Ohio State Univ, Coll Med, Columbus, OH 43210 USA
[4] Drexel Univ, Coll Med, Dept Med, Philadelphia, PA 19104 USA
[5] Univ Penn, Dept Med, Philadelphia, PA 19104 USA
来源
ELIFE | 2019年 / 8卷
基金
美国国家卫生研究院;
关键词
SINGLE-CHANNEL PROPERTIES; BISPECTRAL INDEX; NEURAL INERTIA; POSTOPERATIVE DELIRIUM; RECURRENT NETWORK; MOLECULAR TARGETS; GABA(A) RECEPTORS; SLEEP; CONSCIOUSNESS; MODEL;
D O I
10.7554/eLife.50143
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Traditionally, drug dosing is based on a concentration-response relationship estimated in a population. Yet, in specific individuals, decisions based on the population-level effects frequently result in over or under-dosing. Here, we interrogate the relationship between population-based and individual-based responses to anesthetics in mice and zebrafish. The anesthetic state was assessed by quantifying responses to simple stimuli. Individual responses dynamically fluctuated at a fixed drug concentration. These fluctuations exhibited resistance to state transitions. Drug sensitivity varied dramatically across individuals in both species. The amount of noise driving transitions between states, in contrast, was highly conserved in vertebrates separated by 400 million years of evolution. Individual differences in anesthetic sensitivity and stochastic fluctuations in responsiveness complicate the ability to appropriately dose anesthetics to each individual. Identifying the biological substrate of noise, however, may spur novel therapies, assure consistent drug responses, and encourage the shift from population-based to personalized medicine.
引用
收藏
页数:25
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