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Ground based high time resolution astronomical (HTRA) observations require specialised detectors. Photon counting detectors that combine high spatial resolution imaging with fast event timing capability have been a significant technical challenge. We have developed a high-temporal and -spatial resolution, high-throughput sealed tube microchannel plate detector with electronic readout as a tool for HTRA applications. The design is based on a 25 mm diameter S20 photocathode followed by a microchannel plate stack, read out by a cross delay line anode with timing and imaging electronics. The detector supports 500 kHz global count rate, 10 kHz /100 μm2/sec local count rate, and 100 ps timing resolution. We also describe high time resolution astronomical observations currently being obtained with the NASA GALEX UV satellite, as well as preliminary visible wavelength imaging results obtained on the Crab pulsar at the Lick Observatory. [ABSTRACT FROM AUTHOR]

In the previous chapter we discussed the association between phenotype and genotype for tests based on a single SNP marker. In this chapter we would like to consider tests of association that combine information from several markers. [ABSTRACT FROM AUTHOR]

Association studies are an alternative to linkage analysis as tools for the discovery of genetic factors that may contribute to the susceptibility to a disease. For reasons that will become apparent below, they can also be used in conjunction with linkage analysis to give a much more precise estimate of the location of a gene that has already been mapped to a chromosomal region. Whereas linkage analysis is based on sampling pedigrees and investigating the pattern of inheritance within families, in many approaches to association studies, unrelated genomes are sampled and compared. For example, in the case-control design (CC), samples of affected cases and unaffected controls, unrelated to each other, are collected. The genetic composition of one group is compared with the genetic composition of the other group at a set of genetic markers. Loci which show substantial between-groups divergence are taken to be associated with susceptibility to the disease. [ABSTRACT FROM AUTHOR]

In this chapter we first study QTL mapping in human pedigrees and then consider for qualitative traits some more complicated issues that were not covered in Chap. 9. [ABSTRACT FROM AUTHOR]

Admixture occurs when two or more populations merge to form a new population. A classical example in humans is the African-American population. The African population and the European Caucasian population have diverged during thousands of years of largely separate evolution. During the late eighteenth and early nineteenth centuries, substantial numbers of Africans were brought to the region that became the United States of America, where most lived as slaves of the Caucasian population. Although interracial marriages were rare, substantial genetic blending between those two populations did occur (in addition to some blending with the Native American population). It is estimated that about 20% of the genetic material in today's African-American population originated from a non-African, predominantly a Caucasian, source. [ABSTRACT FROM AUTHOR]

In humans we cannot create inbred lines, backcrosses, etc. Consequently, it is more difficult to study directly the correlation of phenotypes and genetic markers. We can proceed indirectly by noting that relatives frequently have more similar phenotypes than non-relatives, presumably because they have more similar genotypes. For studying human diseases, particularly convenient units are affected sib pairs (ASP), which are the subject of this chapter. We delay until Chap. 11 a discussion of the substantially more complex problem of pedigrees involving variable numbers and relationships of affecteds. [ABSTRACT FROM AUTHOR]

In this chapter we introduce briefly a number of more advanced topics, some of which are of current research interest. Some of the topics involve multidimensional parameters and are closely related to Probs. 5.4 and 6.4, which are concerned with detection of linkage in an intercross when the model permits both an additive and a dominance effect. (See also Prob. 4.3.) In these cases the new problems can be solved by conceptually straightforward extensions of results derived previously. In other cases the analysis becomes substantially more difficult and the results less conclusive, so the discussion here is at best an introduction. [ABSTRACT FROM AUTHOR]

In the preceding chapters we have assumed that all marker genotypes are known exactly. In practice there are often missing genotypes; and even when the genotypes of actual markers are not missing, one can regard the positions between actual markers as potential markers, the genotypes of which are missing. One can then make an attempt to reconstruct the missing information by statistical means. For important reasons that will become apparent in Chap. 9, problems of missing information are even more acute in outbred populations, and in particular humans. In this chapter we introduce, in the relatively simple situation of crosses between inbred strains, some basic techniques that are particularly useful for dealing with different kinds of missing information that arise in problems of gene mapping. In later chapters we will discuss more general approaches that can handle more complex situations. [ABSTRACT FROM AUTHOR]

The significance level is the determining factor in the specification of the rejection region of a statistical test. Only the distribution under the null assumption of no signal plays a role in setting the level of the threshold, once the test statistic and the general form of test are decided upon. However, after setting that threshold, one can examine other statistical properties of the resulting test. A central property is statistical power of the test — the probability to reject the null hypothesis when a signal is present. Since this probability depends on the values of the parameters, one often speaks of the power function to emphasize this dependence. For a test at a single marker, this probability is obtained approximately from the normal distribution; it is a function of the noncentrality parameter given by (4.6). In this chapter we will examine the concept of power for a whole-genome scan. [ABSTRACT FROM AUTHOR]

The task of mapping loci related to a trait is carried out in a number of steps. The aim of the first step is the identification of the chromosome carrying the trait-related polymorphism. Within that chromosome, one finds a wide region which is likely to contain the genetic factor. The second step involves the narrowing down of the region. Finally, once the functional polymorphism has been barricaded within a small enough chromosomal region, the direct examination of polymorphic loci is carried out. An experimental design, which is efficient for one step, may be less efficient for a subsequent step. Therefore, it is useful to apply different experimental resources for each step. Likewise, the statistical tools and the analytic theory may vary from one step to the next. In this and the next chapters we will concentrate on the statistical considerations that are important for the first step: a whole genome scan aimed at the identification of a (relatively wide) chromosomal region containing the functional polymorphism. [ABSTRACT FROM AUTHOR]

In this chapter we introduce the basic principles behind testing a genetic marker for linkage to a quantitative phenotype. We split the presentation into two parts. In the first part we deal with the case of a marker located at a quantitative trait locus (QTL). The parameters that determine the statistical properties of the test are the parameters of the regression model that relates the observed phenotype to the QTL as presented in Chap. 2. Later in this chapter we extend the investigation to the case of a marker in the vicinity of, but not necessarily on top of, the QTL, so the recombination fraction also plays a role. Fortunately the effect of recombination can be separated from the effect of the QTL. From Chaps. 5 onward we discuss the case, which is the common practice today, of testing a set of markers for linkage. [ABSTRACT FROM AUTHOR]

This chapter introduces some concepts of population genetics that are used in various places later in the book. In addition it allows us to expand our knowledge of R functions and to practice conditional probability arguments, which are used here to analyze the genetic makeup of the present generation by conditioning on that of the parental generation. The reader who has a working knowledge of R may wish to skip Sect. 3.1 and the latter part of Sect. 3.2 that refers to Sect. 3.1. The first part of Sect. 3.2 (including the programs "meiosis.rec" and "cross.rec") introduces the concept of recombination, which plays a very important role throughout the book. It can be read independently of Sect. 3.1. Sections 3.3 and 3.4 are important for the third part of the book that deals with human genetics. This chapter contains some relatively difficult mathematical material, which is marked by an asterisk (*) and can be omitted. [ABSTRACT FROM AUTHOR]

Variability in observed phenotypes may result from a variety of factors — inherited as well as environmental. The blend of all these influences gives rise to the unique being every living creature is. Still, the main role of science is to identify the rules which unite seemingly unrelated phenomena. The role of genetics is no different. Its first, and most important, task is to identify the major factors that give rise to different phenotypical characteristics. Once these major factors have been identified, the investigation can be carried on in order to identify genes having secondary effects. [ABSTRACT FROM AUTHOR]

Statistics is the science that formalizes the process of making inferences from observations. Basic to this process of formalization is the concept of a statistical model. In general, a statistical model is an attempt to provide a mathematical simplification of the mechanism that produced the observations. Statistical models are useful since they allow investigation and optimization of the process of analyzing the observations in a context that is wider than the context of the outcome of the specific trial that is being analyzed. For example, it opens the door to considerations such as: "Had we had the opportunity to try a specific inferential procedure on other datasets, all generated by the same statistical mechanism as the one we observe, how would our procedure perform on the average? What would be the probability of drawing an incorrect conclusion?" Such questions are impossible to address unless we adopt a wider point of view. [ABSTRACT FROM AUTHOR]

Leptin is a 16-kDa protein, predominantly produced by adipose tissue with serum leptin concentrations correlating to body fat mass. Initially described as a regulator of appetite, it is now well established that this mediator exerts pro-inflammatory effects on various immune as well as nonimmune cells. In vitro as well as in vivo studies suggest an involvement of leptin in the regulation of intestinal inflammation. The data leading to this finding are the subject of discussion in this chapter. In particular, the various effects of leptin on different cell populations that are involved in the induction and persistence of intestinal inflammation, i.e., T-cells, antigen presenting cells, and epithelial cells, are outlined in detail. In addition, we propose a significant role for the potential interaction of the adipose tissue and the mucosal immune system in the pathophysiology of inflammatory bowel disease. [ABSTRACT FROM AUTHOR]

The temperature/pressure dependency of marine prokaryotes and fungi, in terms of their growth behaviour as well as their potential to produce new metabolites or enzymes, is evaluated. Advanced shake-flask cultivations and controlled bioreactor cultivations following the batch-type, fed-batch-type and/or continuous-type procedures are summarized. After a summary of the fermentation data available so far, values on maximal biomass, specific growth rates, and (sub)optimal production yields are presented. The application of mesophilic microbes, especially bioactive metabolites, to intensify bioprocess engineering studies, is the goal. Cold-active enzymes and thermostable enzymes are the targets of experiments with psychrophilic and hyperthermophilic enzymes. A special challenge to bioengineers is also provided by barophilic strains originating from depths of, say, nearly 11000 m, or from hydrothermal vents. [ABSTRACT FROM AUTHOR]

The Galaxy Evolution Explorer (GALEX) is a Space Ultraviolet Imaging and Spectroscopic Survey Small Explorer mission that will map the star formation history of the universe over 0 < z < 2, a key to our understanding of the formation and evolution of galaxies and the origins of stars and heavy elements. It will provide the critical, missing survey of the z=0 UV universe, bridge the gap between the z=0 and redshifted UV universe explored by large optical telescopes, the Hubble Space Telescope and NGST, and provide the framework and targets for numerous high-priority investigations (HST, FUSE, AXAF, and SIRTF). An Associate Investigator Program will provide opportunities to fully exploit the mission and data potential. In addition to an All-Sky survey in two bands (150 and 240 nm), GALEX will perform a deep imaging survey of 160 square degrees to m(AB)=26, and spectroscopic surveys over a range of depths and sky coverages. These regions are being selected in coordination with other ongoing and planned surveys at other wavelengths, including the visible, near and far-IR and X-ray. GALEX uses the space ultraviolet to derive extinction corrected star formation rates. Slitless grism spectroscopy is highly efficient, providing 100,000 galaxy spectra in one year. The 50 cm telescope, operating from 135-300 nm exploits high-resolution, large-format microchannel-plate detectors and optical coatings to attain the deep, broad-band imaging and spectroscopy required. [ABSTRACT FROM AUTHOR]

Some microorganisms are able to convert preferably carbohydrates, n-alkanes (C10 to C20), and triglycerides (fatty acids of C10 to C22) into glycolipids. The carbon sources may be used separately or in combination with each other. As for biosynthetic pathways, these include both degradation and new synthesis of sugar lipids, as well as direct incorporation, elongation, or modification of precursor molecules. Reviews recently published are those of Desai and Desai (1) and Lang and Wagner (2,3), indicating that in general the following patterns of glycolipid production by microbial cultivation are possible: 1.Growth-associated production.2.Production under growth-limiting conditions.3.Production by resting cells (free or immobilized). [ABSTRACT FROM AUTHOR]

Ductile fracture occurs through growth and coalescence of micro-voids that originate at the location of inclusions and precipitates. The plastic work dissipated in these micro-separation processes leading to the creation of a unit fracture surface area is a measure of the micro-toughness of the material. Furthermore, void growth and coalescence processes are accompanied by plastic deformation of the material surrounding the voids. The energy dissipated by the micro-separation processes of void growth and coalescence, and the plastic deformation in the bulk material surrounding the voids together contribute to the overall fracture toughness of the material. Conventional fracture toughness tests fail to individually measure these two very different contributions. As a result, there is limited transferability of fracture toughness test data from the laboratory to an actual structure. [ABSTRACT FROM AUTHOR]