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

Recent developments in the quantitative analysis of complex networks, based largely on graph theory, have been rapidly translated to studies of brain network organization. The brain's structural and functional systems have features of complex networks--such as small-world topology, highly connected hubs and modularity--both at the whole-brain scale of human neuroimaging and at a cellular scale in non-human animals. In this article, we review studies investigating complex brain networks in diverse experimental modalities (including structural and functional MRI, diffusion tensor imaging, magnetoencephalography and electroencephalography in humans) and provide an accessible introduction to the basic principles of graph theory. We also highlight some of the technical challenges and key questions to be addressed by future developments in this rapidly moving field.

Complex brain networks: graph theoretical analysis of structural and functional systems

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

Complex networks: Structure and dynamics

▪ Abstract Synaptic transmission is a dynamic process. Postsynaptic responses wax and wane as presynaptic activity evolves. This prominent characteristic of chemical synaptic transmission is a crucial determinant of the response properties of synapses and, in turn, of the stimulus properties selected by neural networks and of the patterns of activity generated by those networks. This review focuses on synaptic changes that result from prior activity in the synapse under study, and is restricted to short-term effects that last for at most a few minutes. Forms of synaptic enhancement, such as facilitation, augmentation, and post-tetanic potentiation, are usually attributed to effects of a residual elevation in presynaptic [Ca2+]i, acting on one or more molecular targets that appear to be distinct from the secretory trigger responsible for fast exocytosis and phasic release of transmitter to single action potentials. We discuss the evidence for this hypothesis, and the origins of the different kinetic phases...

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Short-Term Synaptic Plasticity

The emergence of a unified cognitive moment relies on the coordination of scattered mosaics of functionally specialized brain regions. Here we review the mechanisms of large-scale integration that counterbalance the distributed anatomical and functional organization of brain activity to enable the emergence of coherent behaviour and cognition. Although the mechanisms involved in large-scale integration are still largely unknown, we argue that the most plausible candidate is the formation of dynamic links mediated by synchrony over multiple frequency bands.

The brainweb: phase synchronization and large-scale integration.

Rhythmic movements are produced by central pattern-generating networks whose output is shaped by sensory and neuromodulatory inputs to allow the animal to adapt its movements to changing needs. This review discusses cellular, circuit, and computational analyses of the mechanisms underlying the generation of rhythmic movements in both invertebrate and vertebrate nervous systems. Attention is paid to exploring the mechanisms by which synaptic and cellular processes interact to play specific roles in shaping motor patterns and, consequently, movement.

Principles of rhythmic motor pattern generation

Neurons in most animals live a very long time relative to the half-lives of all of the proteins that govern excitability and synaptic transmission. Consequently, homeostatic mechanisms are necessary to ensure stable neuronal and network function over an animal's lifetime. To understand how these homeostatic mechanisms might function, it is crucial to understand how tightly regulated synaptic and intrinsic properties must be for adequate network performance, and the extent to which compensatory mechanisms allow for multiple solutions to the production of similar behaviour. Here, we use examples from theoretical and experimental studies of invertebrates and vertebrates to explore several issues relevant to understanding the precision of tuning of synaptic and intrinsic currents for the operation of functional neuronal circuits.

Variability, compensation and homeostasis in neuron and network function

Central pattern generators and the control of rhythmic movements

Although common sense tells us that no two brains are identical, a series of experimental strategies has evolved, on the basis of studies into the influence of controlled variables on neuronal or network function, that are designed to remove the influence of the underlying variance in neuronal properties and synaptic strengths. These strategies include averaging or normalizing data and comparing each preparation to its own control before and after a treatment. Successful as these strategies may be, they implicitly assume that variability between preparations or animals is ‘experimental noise’ rather than an essential characteristic of the nervous system. We used computational models to study this underlying variability in synaptic strengths and neuronal properties in the production of a simple motor pattern. Specifically, we searched for combinations of synaptic strengths and intrinsic properties in threeneuron model networks that produced output patterns within the range of the pyloric rhythms generated by the stomatogastric ganglia of 99 lobsters (Homarus americanus). Here we argue that network output might be more tightly regulated than many of the underlying cellular and synaptic properties. Previous computational work using models of single neurons has shown that similar electrical activity can be achieved with varying combinations of ion channels in the neuron’s membrane 1–4 . Experimental measurements of single membrane currents in the same individually identified neurons in different preparations show severalfold ranges in conductance densities 2,3,5 . Together, these data suggest that individual neurons ‘tune’ themselves to achieve combinations of conductance densities that are consistent with a given target excitability 6–9 . This conceptual framework fits with the compensation that occurs after genetic manipulation of channelgene expression, as alterations in the expression of one channel may be compensated by changes in the density of one or more other channels 10 . We also argue that compensation may occur at the network level as well: that is, each animal’s network has a target activity level, and mechanisms exist that allow each animal to produce a target network performance despite having differing sets of synaptic strengths and intrinsic membrane properties. The present study supports this notion by demonstrating that similar and functional network behavior can result from widely differing combinations of intrinsic and synaptic properties. RESULTS The pyloric rhythm of the crustacean stomatogastric ganglion (STG) is an ideal test bed for studies of how network performance depends on the properties of the neurons and synapses within a functional circuit 11 . Unlike many preparations with relatively ill-defined outputs or connectivity, this ganglion has a small number of neurons and a stereotyped motor pattern, making it relatively easy to determine when and how network behavior is influenced by changes in synaptic strength or intrinsic membrane properties 12,13 .

/pdf/similar-network-activity-from-disparate-circuit-parameters-19o60e6ia8.pdf

Eve Marder

Papers

Principles of rhythmic motor pattern generation

Variability, compensation and homeostasis in neuron and network function

Central pattern generators and the control of rhythmic movements

Similar network activity from disparate circuit parameters.

Neuromodulation of Neuronal Circuits: Back to the Future