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

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

Complex networks: Structure and dynamics

Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

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.

We use the concept of phase synchronization for the analysis of noisy nonstationary bivariate data. Phase synchronization is understood in a statistical sense as an existence of preferred values of the phase difference, and two techniques are proposed for a reliable detection of synchronous epochs. These methods are applied to magnetoencephalograms and records of muscle activity of a Parkinsonian patient. We reveal that the temporal evolution of the peripheral tremor rhythms directly reflects the time course of the synchronization of abnormal activity between cortical motor areas.

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Detection of n:m Phase Locking from Noisy Data: Application to Magnetoencephalography

The coordinated reset of neural subpopulations is introduced as an effectively desynchronizing stimulation technique. For this, short sequences of high-frequency pulse trains are administered at different sites in a coordinated way. Desynchronization is easily maintained by performing a coordinated reset with demand-controlled timing or by periodically administering resetting high-frequency pulse trains of demand-controlled length. Unlike previously developed methods, this novel approach is robust against variations of model parameters and does not require time-consuming calibration. The novel technique is suggested to be used for demand-controlled deep brain stimulation in patients suffering from Parkinson's disease or essential tremor. It might even be applicable to diseases with intermittently emerging synchronized neural oscillations like epilepsy.

A model of desynchronizing deep brain stimulation with a demand-controlled coordinated reset of neural subpopulations

Phase Resetting in Medicine and Biology

Synchronization of coupled oscillating systems means appearance of certain relations between their phases and frequencies. Here we use this concept in order to address the inverse problem and to reveal interaction between systems from experimental data. We discuss how the phases and frequencies can be estimated from time series and present techniques for detection and quantification of synchronization. We apply our approach to human posture control data of healthy subjects and neurological patients, to multichannel magnetoencephalography data and records of muscle activity of a Parkinsonian patient, and also use it to analyse the cardiorespiratory interaction in humans. By means of these examples we demonstrate that our method is effective for the analysis of systems interrelation from noisy nonstationary bivariate data and provides other information than traditional correlation (spectral) techniques. Published in: Handbook of Biological Physics, Elsevier Science, Series Editor A.J. Hoff, Vol. 4, Neuro-informatics, Editors: F. Moss and S. Gielen, Chapter 9, pp. 279-321, 2001. Preprint submitted to Elsevier Preprint 14 August 2001

/pdf/phase-synchronization-from-theory-to-data-analysis-3rxlkuby63.pdf

Phase synchronization: from theory to data analysis

Resetting an Ensemble of Oscillators.- Synchronization Patterns.- Stochastic Model.- Clustering in the Presence of Noise.- Single Pulse Stimulation.- Periodic Stimulation.- Data Analysis.- Modelling Perspectives.- Neurological Perspectives.- Epilogue.

Peter A. Tass

Papers

Detection of n:m Phase Locking from Noisy Data: Application to Magnetoencephalography

A model of desynchronizing deep brain stimulation with a demand-controlled coordinated reset of neural subpopulations

Phase Resetting in Medicine and Biology

Phase synchronization: from theory to data analysis

Phase Resetting in Medicine and Biology: Stochastic Modelling and Data Analysis