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James J. Collins

Bio: James J. Collins is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Synthetic biology & Population. The author has an hindex of 151, co-authored 669 publications receiving 89476 citations. Previous affiliations of James J. Collins include Baylor College of Medicine & University at Albany, SUNY.


Papers
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Journal ArticleDOI
TL;DR: Noise can enhance the detection and transmission of weak signals in certain nonlinear systems, via a mechanism known as stochastic resonance, and input noise can be used to improve motor control in humans by applying subsensory mechanical noise to the feet.
Abstract: Noise can enhance the detection and transmission of weak signals in certain nonlinear systems, via a mechanism known as stochastic resonance. Here we show that input noise can be used to improve motor control in humans. Specifically, we show that the postural sway of both young and elderly individuals during quiet standing can be significantly reduced by applying subsensory mechanical noise to the feet. We further demonstrate with input noise a trend towards the reduction of postural sway in elderly subjects to the level of young subjects. These results suggest that noise-based devices, such as randomly vibrating shoe inserts, may enable people to overcome functional difficulties due to age-related sensory loss.

350 citations

Journal ArticleDOI
TL;DR: Whether subsensory mechanical noise applied to the soles of the feet via vibrating insoles can be used to improve quiet‐standing balance control in patients with diabetic neuropathy and patients with stroke is investigated.
Abstract: Objective Somatosensory function declines with diabetic neuropathy and often with stroke, resulting in diminished motor performance. Recently, it has been shown that input noise can enhance human sensorimotor function. The goal of this study was to investigate whether subsensory mechanical noise applied to the soles of the feet via vibrating insoles can be used to improve quiet-standing balance control in 15 patients with diabetic neuropathy and 15 patients with stroke. Sway data of 12 healthy elderly subjects from a previous study on vibrating insoles were added for comparison. Methods Five traditional sway parameters and three sway parameters from random-walk analysis were computed for each trial (no noise or noise). Results Application of noise resulted in a statistically significant reduction in each of the eight sway parameters in the subjects with diabetic neuropathy, the subjects with stroke, and the elderly subjects. We also found that higher levels of baseline postural sway in sensory-impaired individuals was correlated with greater improvements in balance control with input noise. Interpretation This work indicates that noise-based devices could ameliorate diabetic and stroke impairments in balance control. Ann Neurol 2006

343 citations

Journal ArticleDOI
03 Aug 2012-Cell
TL;DR: In this article, a synthetic framework for systematically constructing eukaryotic transcription functions using artificial zinc fingers, modular DNA-binding domains found within many eUKaryotic TFs, is presented.

341 citations

Journal ArticleDOI
TL;DR: This work demonstrates that E. coli can be engineered into living diagnostics capable of nondestructively probing the mammalian gut and lays a foundation for the use of synthetic genetic circuits as monitoring systems in complex, ill-defined environments.
Abstract: The mammalian gut is a dynamic community of symbiotic microbes that interact with the host to impact health, disease, and metabolism. We constructed engineered bacteria that survive in the mammalian gut and sense, remember, and report on their experiences. Based on previous genetic memory systems, we constructed a two-part system with a “trigger element” in which the lambda Cro gene is transcribed from a tetracycline-inducible promoter, and a “memory element” derived from the cI/Cro region of phage lambda. The memory element has an extremely stable cI state and a Cro state that is stable for many cell divisions. When Escherichia coli bearing the memory system are administered to mice treated with anhydrotetracycline, the recovered bacteria all have switched to the Cro state, whereas those administered to untreated mice remain in the cI state. The trigger and memory elements were transferred from E. coli K12 to a newly isolated murine E. coli strain; the stability and switching properties of the memory element were essentially identical in vitro and during passage through mice, but the engineered murine E. coli was more stably established in the mouse gut. This work lays a foundation for the use of synthetic genetic circuits as monitoring systems in complex, ill-defined environments, and may lead to the development of living diagnostics and therapeutics.

337 citations

Journal ArticleDOI
TL;DR: A gradient model of oncogenic NRAS signaling in which the output is gated, resulting in the decoupling of discrete downstream biological phenotypes as a result of incomplete inhibition is suggested, offering a new framework to identify nonobvious coextinction target(s) for combined pharmacological inhibition in NRAS-mutant melanomas.
Abstract: NRAS-driven melanomas have limited therapeutic options. Combining genetically engineered models and oncogenic signaling inhibitors with rational systems-biology approaches, the authors compare the effects of genetic extinction of NRAS to that of chemical pathway inhibition targeting downstream MEK. The differences provide actionable targets by revealing that NRAS signaling operates as a gated output and that MEK inhibition, although inducing apoptosis, is not able to achieve further inhibition of NRAS-induced outputs such as cell-cycle progression. A combination of MEK and CDK4 inhibitors provides a more complete inhibition of NRAS signaling and a more effective antitumor effect in vivo.

337 citations


Cited by
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Journal ArticleDOI
04 Jun 1998-Nature
TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
Abstract: Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks 'rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them 'small-world' networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation. The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.

39,297 citations

28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
TL;DR: In this paper, a simple model based on the power-law degree distribution of real networks was proposed, which was able to reproduce the power law degree distribution in real networks and to capture the evolution of networks, not just their static topology.
Abstract: The emergence of order in natural systems is a constant source of inspiration for both physical and biological sciences. While the spatial order characterizing for example the crystals has been the basis of many advances in contemporary physics, most complex systems in nature do not offer such high degree of order. Many of these systems form complex networks whose nodes are the elements of the system and edges represent the interactions between them. Traditionally complex networks have been described by the random graph theory founded in 1959 by Paul Erdohs and Alfred Renyi. One of the defining features of random graphs is that they are statistically homogeneous, and their degree distribution (characterizing the spread in the number of edges starting from a node) is a Poisson distribution. In contrast, recent empirical studies, including the work of our group, indicate that the topology of real networks is much richer than that of random graphs. In particular, the degree distribution of real networks is a power-law, indicating a heterogeneous topology in which the majority of the nodes have a small degree, but there is a significant fraction of highly connected nodes that play an important role in the connectivity of the network. The scale-free topology of real networks has very important consequences on their functioning. For example, we have discovered that scale-free networks are extremely resilient to the random disruption of their nodes. On the other hand, the selective removal of the nodes with highest degree induces a rapid breakdown of the network to isolated subparts that cannot communicate with each other. The non-trivial scaling of the degree distribution of real networks is also an indication of their assembly and evolution. Indeed, our modeling studies have shown us that there are general principles governing the evolution of networks. Most networks start from a small seed and grow by the addition of new nodes which attach to the nodes already in the system. This process obeys preferential attachment: the new nodes are more likely to connect to nodes with already high degree. We have proposed a simple model based on these two principles wich was able to reproduce the power-law degree distribution of real networks. Perhaps even more importantly, this model paved the way to a new paradigm of network modeling, trying to capture the evolution of networks, not just their static topology.

18,415 citations

Journal ArticleDOI
TL;DR: In this paper, Imagined communities: Reflections on the origin and spread of nationalism are discussed. And the history of European ideas: Vol. 21, No. 5, pp. 721-722.

13,842 citations

Journal ArticleDOI
Stephen S Lim1, Theo Vos, Abraham D. Flaxman1, Goodarz Danaei2  +207 moreInstitutions (92)
TL;DR: In this paper, the authors estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010.

9,324 citations