The role of antibodies in multiple sclerosis

B cells, plasma cells, and antibodies are commonly found in active central nervous system (CNS) lesions in patients with multiple sclerosis (MS). B cells isolated from CNS lesions as well as from the cerebrospinal fluid (CSF) show signs of clonal expansion and hypermutation, suggesting their local activation. Plasma blasts and plasma cells maturating from these B cells were recently identified to contribute to the development of oligoclonal antibodies produced within the CSF, which remain a diagnostic hallmark finding in MS. Within the CNS, antibody deposition is associated with complement activation and demyelination, indicating antigen recognition-associated effector function. While some studies indeed implied a disease-intrinsic and possibly pathogenic role of antibodies directed against components of the myelin sheath, no unequivocal results on a decisive target antigen within the CNS persisted to date. The notion of a pathogenic role for antibodies in MS is nevertheless empirically supported by the clinical benefit of plasma exchange in patients with histologic signs of antibody deposition within the CNS. Further, such evidence derives from the animal model of MS, experimental autoimmune encephalomyelitis (EAE). In transgenic mice endogenously producing myelin-specific antibodies, EAE severity was substantially increased accompanied by enhanced CNS demyelination. Further, genetic engineering in mice adding T cells that recognize the same myelin antigen resulted in spontaneous EAE development, indicating that the coexistence of myelin-specific B cells, T cells, and antibodies was sufficient to trigger CNS autoimmune disease. In conclusion, various pathological, clinical, immunological, and experimental findings collectively indicate a pathogenic role of antibodies in MS, whereas several conceptual challenges, above all uncovering potential target antigens of the antibody response within the CNS, remain to be overcome.     

Dependence of folding dynamics and structural stability on the location of a hydrophobic pair in beta-hairpins

We study the dependence of folding time, nucleation site, and stability of a model beta-hairpin on the location of a cross-strand hydrophobic pair, using a coarse-grained off-lattice model with the aid of Monte Carlo simulations. Our simulations have produced 6500 independent folding trajectories dynamically, forming the basis for extensive statistical analysis. Four folding pathways, zipping-out, middle-out, zipping-in, and reptation, have been closely monitored and discussed in all seven sequences studied. A hydrophobic pair placed near the beta-turn or in the middle section effectively speed up folding; a hydrophobic pair placed close to the terminal ends or next to the beta-turn encourages stability of the entire chain.     

Role of a reaction coordinate in free energy calculations

Abstract

The free energy calculation method emerges as a viable technique for ‘in-silico’ calorimetry. Efficient sampling techniques and the good choice of a reaction path connecting the reactant and the product state enable accurate computations of the free energy differences. We argue that in many cases the thermodynamic integration technique has the lowest variance when the transformation between the reactant and the product state proceeds along the natural path of the studied chemical reaction. We provide examples of free energy calculations for the fragmentation of the charged clusters and the swapping reaction of oligomer formation in proteins that follow a tentative reaction mechanism.     

Thoughts on the origin and nature of life and intelligence on earth

Believing, for good reasons, that our Universe engenders the occurrence of Life, it is probable that Life appeared more than once on young planet Earth. The universality of our genetic code indicates though, that only one line produced a population that was cellular, autopoietic, responsive intelligently (i.e., to its advantage) to its environment, and capable of reproduction. Its evolution took time during which other intermediate or incipient forms of life disappeared. Trying to retrace ab initio the preceding chemical evolution on our young planet, we may not repeat the chemistry which led to our line. One can argue that it may be profitable to attempt to construct artificial life forms using the kind of building blocks that we learned to know through studying the chemistry of our life. Independently, computers are being built, or are planned, which possess memory that can be used appropriately (intelligently), and which to some extent can repair and reproduce themselves. Such Life does not depend on our biochemistry. However, these machines do perform as yet only partly along the lines of our human intelligence which is guided by self-awareness and a sense of individual integrity, and are thereby not equipped to search for Understanding and Self-expression.     

Relating Phylogenetic Trees to Transmission Trees of Infectious Disease Outbreaks

Transmission events are the fundamental building blocks of the dynamics of any infectious disease. Much about the epidemiology of a disease can be learned when these individual transmission events are known or can be estimated. Such estimations are difficult and generally feasible only when detailed epidemiological data are available. The genealogy estimated from genetic sequences of sampled pathogens is another rich source of information on transmission history. Optimal inference of transmission events calls for the combination of genetic data and epidemiological data into one joint analysis. A key difficulty is that the transmission tree, which describes the transmission events between infected hosts, differs from the phylogenetic tree, which describes the ancestral relationships between pathogens sampled from these hosts. The trees differ both in timing of the internal nodes and in topology. These differences become more pronounced when a higher fraction of infected hosts is sampled. We show how the phylogenetic tree of sampled pathogens is related to the transmission tree of an outbreak of an infectious disease, by the within-host dynamics of pathogens. We provide a statistical framework to infer key epidemiological and mutational parameters by simultaneously estimating the phylogenetic tree and the transmission tree. We test the approach using simulations and illustrate its use on an outbreak of foot-and-mouth disease. The approach unifies existing methods in the emerging field of phylodynamics with transmission tree reconstruction methods that are used in infectious disease epidemiology.     

多发性硬化与病毒感染研究进展

多发性硬化发病机制复杂,病毒感染在其发病中可能起着举足轻重的作用,目前多项研究支持他们之间的关联性;分子模拟、免疫调节网络的失调、表位扩展、旁路激活、超抗原激活和直接细胞损伤等是病毒感染导致多发性硬化发病的主要机理。本文就相关研究进行综述。     

Sample size reestimation by Bayesian prediction

We review a Bayesian predictive approach for interim data monitoring and propose its application to interim sample size reestimation for clinical trials. Based on interim data, this approach predicts how the sample size of a clinical trial needs to be adjusted so as to claim a success at the conclusion of the trial with an expected probability. The method is compared with predictive power and conditional power approaches using clinical trial data. Advantages of this approach over the others are discussed.     

Dosimetric characterization of the 60Co BEBIG Co0.A86 high dose rate brachytherapy source using PENELOPE

⁶⁰Co sources are being used as an alternative to ¹⁹²Ir sources in high dose rate brachytherapy treatments. In a recent document from AAPM and ESTRO, a consensus dataset for the ⁶⁰Co BEBIG (model Co0.A86) high dose rate source was prepared by using results taken from different publications due to discrepancies observed among them. The aim of the present work is to provide a new calculation of the dosimetric characteristics of that ⁶⁰Co source according to the recommendations of the AAPM and ESTRO report. Radial dose function, anisotropy function, air-kerma strength, dose rate constant and absorbed dose rate in water have been calculated and compared to the results of previous works. Simulations using the two different geometries considered by other authors have been carried out and the effect of the cable density and length has been studied.     

On the Bayesian estimation of a closed population size in the presence of heterogeneity and model uncertainty

Summary .   We consider the estimation of the size of a closed population, often of interest for wild animal populations, using a capture–recapture study. The estimate of the total population size can be very sensitive to the choice of model used to fit to the data. We consider a Bayesian approach, in which we consider all eight plausible models initially described by Otis et al. (1978, Wildlife Monographs 62, 1–135) within a single framework, including models containing an individual heterogeneity component. We show how we are able to obtain a model-averaged estimate of the total population, incorporating both parameter and model uncertainty. To illustrate the methodology we initially perform a simulation study and analyze two datasets where the population size is known, before considering a real example relating to a population of dolphins off northeast Scotland.