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

We have developed a simple and highly efficient method to disrupt chromosomal genes in Escherichia coli in which PCR primers provide the homology to the targeted gene(s). In this procedure, recombination requires the phage lambda Red recombinase, which is synthesized under the control of an inducible promoter on an easily curable, low copy number plasmid. To demonstrate the utility of this approach, we generated PCR products by using primers with 36- to 50-nt extensions that are homologous to regions adjacent to the gene to be inactivated and template plasmids carrying antibiotic resistance genes that are flanked by FRT (FLP recognition target) sites. By using the respective PCR products, we made 13 different disruptions of chromosomal genes. Mutants of the arcB, cyaA, lacZYA, ompR-envZ, phnR, pstB, pstCA, pstS, pstSCAB-phoU, recA, and torSTRCAD genes or operons were isolated as antibiotic-resistant colonies after the introduction into bacteria carrying a Red expression plasmid of synthetic (PCR-generated) DNA. The resistance genes were then eliminated by using a helper plasmid encoding the FLP recombinase which is also easily curable. This procedure should be widely useful, especially in genome analysis of E. coli and other bacteria because the procedure can be done in wild-type cells.

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One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products

THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.

Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal

Introduction: Migraine is a debilitating primary headache disorder with a poorly understood aetiology. An extensive body of literature supports the theory of migraine as a systemic vascular inflammatory disorder characterised by endothelial dysfunction. It is also well-known that chronic inflammation results in an excessive burden of oxidative stress and therefore cellular dysfunction. In this study the effects of excessive oxidative stress through the phases of female migraine-with-aura (FMA) were evaluated by examining the health of the systems of haemostasis. Methods: Blood was obtained from 11 FMA patients at baseline and during the headache phase of migraine, as well as from 8 healthy age-matched female controls. Samples were analysed using thromboelastography (TEG) to evaluate viscoelastic profiles, light microscopy for erythrocyte morphology, Scanning Electron Microscopy (SEM) for erythrocyte and fibrin clot structure, confocal microscopy for β-amyloid detection in fibrin clots. Results: Viscoelastic profiles from platelet poor plasma showed decreased clot reaction times in FMA at baseline (95% CI [5.56, 8.41]) vs. control (95% CI [7.22, 11.68]); as well as decreased time to maximum thrombus generation for the same comparison (95% CI [6.78, 10.20] vs. [8.90, 12.96]). Morphological analysis of erythrocytes indicated widespread macrocytosis, poikilocytosis and eryptosis in the migraineurs. Analysis of fibrin networks indicated that this hypercoagulability may be a result of aberrant fibrin polymerisation kinetics caused by the adoption of a β-amyloid conformation of fibrin(ogen). Conclusion: The results reaffirm the hypercoagulable state in migraine, and would suggest that this state is most likely a result of a systemic inflammatory state which induces oxidative damage to both erythrocytes and fibrin(ogen) in female episodic migraine-with-aura. Furthermore, if the amylodogenic changes to fibrin(ogen) were observed in a larger cohort, this would support theories of micro-embolisation in migraine-with-aura.

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A Possible Role of Amyloidogenic Blood Clotting in the Evolving Haemodynamics of Female Migraine-With-Aura: Results From a Pilot Study

Pyrolysis mass spectrometry (PyMS) was used to produce biochemical fingerprints from replicate frozen cell cultures of mouse macrophage hybridoma 2C11-12, human leukaemia K562, baby hamster kidney BHK 21/C13, and mouse tumour BW-O, and a fresh culture of Chinese hamster ovary CHO cells. The dimensionality of these data was reduced by the unsupervised feature extraction pattern recognition technique of auto-associative neural networks. The clusters observed were compared with the groups obtained from the more conventional statistical approaches of hierarchical cluster analysis. It was observed that frozen and fresh cell line cultures gave very different pyrolysis mass spectra. When only the frozen animal cells were analysed by PyMS, auto-associative artificial neural networks (ANNs) were employed to discriminate between them successfully. Furthermore, very similar classifications were observed when the same spectral data were analysed using hierarchical cluster analysis. We demonstrate that this approach can detect the contamination of cell lines with low numbers of bacteria and fungi; this approach could plausibly be extended for the rapid detection of mycoplasma infection in animal cell lines. The major advantages that PyMS offers over more conventional methods used to type cell lines and to screen for microbial infection, such as DNA fingerprinting, are its speed, sensitivity and the ability to analyse hundreds of samples per day. We conclude that the combination of PyMS and ANNs can provide a rapid and accurate discriminatory technique for the authentication of animal cell line cultures.

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Rapid authentication of animal cell lines using pyrolysis mass spectrometry and auto-associative artificial neural networks.

III has a mol.wt. of less than 7000 or alternatively that its structure is such that it is strongly bound to and retarded on Sephadex columns. About 90% of the enzyme activity placed on the column was recovered. The material in fraction I when rechromatographed on Sephadex G-100 under the same conditions separated again into three peaks of activity in which the last peak predominated (Fig. I). Peak III has properties associated with enzyme proteins in general. The optimum pH for enzyme activity is 8.2 (Fig. 2a). The enzyme is relatively heat-stable, losing activity at temperatures in excess of 45°C (Fig. 2b).

Evidence from 31P nuclear magnetic resonance that polyphosphate synthesis is a slip reaction in Paracoccus denitrificans [proceedings].

Cheques and balances

Quantitative data on the dynamic changes in the transcriptome and the metabolome of yeast in response to an impulse-like perturbation in nutrient availability was integrated with the metabolic pathway information in order to elucidate the long-term dynamic re-organization of the cells. This study revealed that, in addition to the dynamic re-organization of the de novo biosynthetic pathways, salvage pathways were also re-organized in a time-dependent manner upon catabolite repression. The transcriptional and the metabolic responses observed for nitrogen catabolite repression were not as severe as those observed for carbon catabolite repression. Selective up- or down regulation of a single member of a paralogous gene pair during the response to the relaxation from nutritional limitation was identified indicating a differentiation of functions among paralogs. Our study highlighted the role of inosine accumulation and recycling in energy homeostasis and indicated possible bottlenecks in the process.

Douglas B. Kell

Papers

A Possible Role of Amyloidogenic Blood Clotting in the Evolving Haemodynamics of Female Migraine-With-Aura: Results From a Pilot Study

Rapid authentication of animal cell lines using pyrolysis mass spectrometry and auto-associative artificial neural networks.

Evidence from 31P nuclear magnetic resonance that polyphosphate synthesis is a slip reaction in Paracoccus denitrificans [proceedings].

Cheques and balances

Short- and long-term dynamic responses of the metabolic network and gene expression in yeast to a transient change in the nutrient environment.