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.

/pdf/collective-dynamics-of-small-world-networks-205zhem3gm.pdf

Collective dynamics of small-world networks

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。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

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.

/pdf/statistical-mechanics-of-complex-networks-1zfjpvxipu.pdf

Statistical mechanics of complex networks

Imagined communities: Reflections on the origin and spread of nationalism

https://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736(12)61766-8.pdf

A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010

https://doi.org/10.1016/j.curtheres.2022.100667

Feasibility study of Bismuth Subsalicylate (BSS) as an addition to standard of care for COVID-19 therapy

Work under the rubric of literacy practices is usefully understood as part of a general commitment to analyze micro and macro relationships. This is done under the concept of ‘practice,’ seen as the intersection point of person, culture, and society. In the self-defined New Literacy Studies, analysis of literacy practices entails a dual focus on both events and models or theories. This article discusses these foci in light of sociocultural phenomena such as artifactualized language, ideology, subversive language use, and institutional authority. It concludes by discussing contemporary literacy problems and recommending continuing exchanges between the New Literacy Studies and anthropologically based research on indexicals.

Literacy Practices in Sociocultural Perspective

Spike-frequency adaptation improves noise-shaping in model neuronal networks

Schistosomiasis, caused by the blood fluke Schistosoma , is a devastating and widespread disease affecting more than 200 million people and threatening over 700 million people worldwide. Treatment relies exclusively on one drug, praziquantel, for which there are concerns of emerging drug resistance and which has shown some limitations in mass drug administration programs. Efforts to develop an effective vaccine to combat schistosomiasis have been unsuccessful; thus, there is an urgent need for alternative drugs and better prevention strategies. Here we report the discovery and purification of a novel tetracyclic alkaloid secreted by the rotifer Rotaria rotatoria , which lives commensally on snails that serve as intermediate hosts for S. mansoni . This compound effectively paralyzes cercariae, the infective larvae of schistosomes, at nanomolar concentrations. Furthermore, we show that worm burden and disease pathology are significantly reduced when cercariae are pre-treated with this Schistosome Paralysis Factor (SPF). Identifying this molecule provides new directions for understanding motility of schistosome cercariae and new strategies for preventing schistosomiasis.

https://www.biorxiv.org/content/biorxiv/early/2018/09/27/426999.full.pdf

James J. Collins

Papers

Feasibility study of Bismuth Subsalicylate (BSS) as an addition to standard of care for COVID-19 therapy

Literacy Practices in Sociocultural Perspective

Spike-frequency adaptation improves noise-shaping in model neuronal networks

Data for A novel rotifer derived alkaloid paralyzes schistosome larvae and prevents infection

Carbohydrate Ingestion During Exhaustive High-intensity Intermittent Shuttle Running In The Heat: 58 10:45 AM - 11:00 AM