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

Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

The Theory of Island Biogeography

http://www.maths.qmul.ac.uk/%7Elatora/report_06.pdf

Complex networks: Structure and dynamics

https://www.tau.ac.il/%7Eklafter1/258.pdf

The random walk's guide to anomalous diffusion: a fractional dynamics approach

The fundamental idea developed throughout this short overview on Economic Complexity is that a revolution of the revolution of Economics is needed to turn this field into a mature discipline. The first revolution of Economic Complexity (Bouchaud in Nature 455:1181, 2008) led to a conceptual paradigm shift and agent-based models have shown, from a qualitative point of view, the crucial role played by concepts like agent heterogeneity and herding behavior to understand the non-trivial features of financial time series. The second revolution must lead the paradigm shift from a conceptual and qualitative level to a quantitative and effective description of economic systems. This can be achieved through the introduction of new metrics and quantitative methods in Social Sciences (Economics, Finance, opinion dynamics, etc.). In fact, the concept of metrics is usually neglected by mainstream theories of Economy and Finance. Only in that way Economic Complexity can concretely affect the thinking of Economic mainstream and, in this sense, become a mature discipline. The large availability of datasets (the so-called Big Data Science) has recently revealed new promising path towards such perspectives and, as an example, we briefly discuss how archival data about export flows can be turned into a concrete tool to assess the competitiveness of countries and the complexity of products.

An Overview of the New Frontiers of Economic Complexity

The inclusion of nonadiabatic corrections to the electron-phonon interaction leads to a strong momentum dependence in the generalized Eliashberg equations beyond Migdal's limit. For a s-wave symmetry of the order parameter, this induced momentum dependence leads to an enhancement of Tc when small momentum transfer is dominant. Here we study how the d-wave symmetry affects the above behavior. We find that the nonadiabatic corrections depend only weakly on the symmetry of the order parameter provided that only small momentum scatterings are allowed for the electron-phonon interaction. In this situation, We show that also for a d-wave symmetry of the order parameter, the nonadiabatic corrections enhance Tc. We also discuss the possible interplay and crossover between s- and d-wave depending on the material's parameters.

https://arxiv.org/pdf/cond-mat/0005217.pdf

d-wave nonadiabatic superconductivity

We address local inelastic scattering from the vibrational impurity adsorbed onto graphene and the evolution of the local density of electron states near the impurity from a weak to strong coupling ...

/pdf/inelastic-electron-tunneling-spectroscopy-at-local-defects-1ucsrstf8i.pdf

Inelastic electron tunneling spectroscopy at local defects in graphene

In this paper we present a generalized model for network growth that links the microscopical agent strategies with the large scale behavior This model is intended to reproduce the largest number of features of the Internet network at the Autonomous System (AS) level Our model of network grows by adding both new vertices and new edges between old vertices In the latter case a ``rewarding attachment'' takes place mimicking the disassortative mixing between small routers to larger ones We find a good agreement between experimental data and the model for the degree distribution, the betweenness distribution, the clustering coefficient and the correlation functions for the degrees

https://arxiv.org/pdf/cond-mat/0307610.pdf

Generalized Network Growth: from Microscopic Strategies to the Real Internet Properties

We study the properties of the growth probabilities for diffusion limited aggregation and the dielectric breakdown model in the steady state regime of the cylinder geometry. The results show a rather unambiguous picture with the following properties: The projection of the growth probability along the growth direction is exponential , contrary to the Gaussian behavior of the radial case. One can distinguish two regions, one with simple multifractal properties corresponding to the growing zone and a second one which accounts for the exponential decay of the growth probability. This situation can be explained in terms of a first order transition in the multifractal spectrum at q = 1. This corresponds to a different picture with respect to those that have been proposed in the literature. The properties of the growing interface could be universal while the small probability part is non-universal and it depends on the particular geometry. However, we can show that this part is irrelevant with respect to the growth process, even though it is determined by it.

Luciano Pietronero

Papers

An Overview of the New Frontiers of Economic Complexity

d-wave nonadiabatic superconductivity

Inelastic electron tunneling spectroscopy at local defects in graphene

Generalized Network Growth: from Microscopic Strategies to the Real Internet Properties

Properties of the growth probability for the dielectric breakdown model in cylinder geometry