Academic literature on the topic 'Contrat incomplet et la cause'

Text about genes can be effectively leveraged to enhance sequence analysis (MacCallum, Kelley et al. 2000; Chang, Raychaudhuri et al. 2001; McCallum and Ganesh 2003; Eskin and Agichtein 2004; Tu, Tang et al. 2004). Most of the emerging methods utilize textual representations similar to the one we introduced in the previous chapter. To analyze sequences, a numeric vector that contains information about the counts of different words in references about that sequence can be used in conjunction with the actual sequence information. Experienced biologists understand the value of using the information in scientific text during sequence searches, and commonly use scientific text and annotations to guide their intuition. For example, after a quick BLAST search, a trained expert might quickly look over the hits and their associated annotations and literature references and assess the validity of the hits. The apparently valid sequence hits can then be used to draw conclusions about the query sequence by transferring information from the hits. In most cases, the text serves as a proxy for structured functional information. High quality functional annotations that succinctly and thoroughly describe the function of a protein are often unavailable. Defining appropriate keywords for a protein requires a considerable amount of effort and expertise, and in most cases, the results are incomplete as there is an evergrowing collection of knowledge about proteins. So, one option is to use text to compare the biological function of different sequences instead. There are different ways in which the functional information in text could be used in the context of sequence analysis. One possibility is to first run a sequence analysis algorithm, and then to use text profiles to summarize or organize results. Functional keywords can be assigned to the whole group of hit sequences. Additionally, given a series of sequences, they can be grouped according to like function. In either case, quick assessment of the content of text associated with sequences offers insight about exactly what we are seeing. These approaches are particularly useful if we are querying a large database of sequences with a novel sequence that we have very little information about.

Serpentine substrates are found in many parts of the world, but there is considerable variation in the structure, composition, and diversity of the flora they support. To place western North America in a worldwide context, this chapter provides a brief sketch of global patterns in serpentine plant life, drawing on the reviews by Brooks (1987), Baker et al. (1992), and Roberts and Proctor (1992), as well as other sources. Following this is an overview of some of the main physical factors known to cause variation in the vegetation on serpentine both at the regional and local levels. Finally, we discuss what is known about the roles of competition, fire, herbivory, and other ecological processes in shaping plant assemblages on serpentine. The availability of botanical information varies considerably around the world. In most countries where serpentine occurs, it is possible to name at least some of the plant species and vegetation types found on it. But in countries where surveys are incomplete, or where information has not been synthesized at a national or larger level, it is generally not possible to estimate the number of serpentine-endemic taxa or to describe patterns of variation within the serpentine vegetation. Indonesia, Malaysia, the Phillippines, and Brazil are particularly notable as countries with serpentine floras that are potentially rich but in need of more study. With this caveat, however, some of the major global trends can be described based on available knowledge. Flora and vegetation of selected parts of the world are summarized in table 10-1, and global contrasts between the vegetation of serpentine and other soils are summarized in table 10-2. New Caledonia and Cuba lead the world in known serpentine endemic diversity with 900+ species each, >90% of which are also endemics to these islands. Depending on elevation, rainfall, and fire history, the serpentine vegetation on both islands varies from sclerophyllous scrubland that contrasts visibly with the neighboring vegetation, to medium-stature rainforest that is not strikingly different in appearance from the vegetation growing in other soils.

Bacteria are unstable when the temperature or pressure is sufficiently high. Their inactivation by pressure is the result of a complicated interplay of both temperature and pressure effects. The p-T stability diagram of bacteria is similar to that of proteins. But inactivation kinetics of bacteria indicate that the lethal event cannot be the denaturation of the most sensitive proteins in the cell. For in that case one would expect a lag time followed by a sudden inactivation when the last copy of those sensitive proteins was destroyed. On the contrary, it appears as if the kinetics is caused by a single damage mechanism. In addition, some evidence suggests that the membrane is involved. Therefore, it seems that membrane-associated proteins play a major role in the activation of bacteria. The inactivation of bacterial spores shows an even more complex T-p interrelationship. The reason is that two different processes are combined in spore inactivation: the germination of dormant spores at comparatively low pressures and the inactivation of the germinated specimens at high pressures. Thus, special procedures are needed for effective spore inactivation. Microorganisms are killed when the surrounding hydrostatic pressure is sufficiently high. This finding provides the basis for developing a physical sterilization method for drugs and food. Initial experiments in this area were carried out nearly 100 years ago (Hite, 1899), but technical shortcomings and incomplete scientific knowledge impeded their utilization at that time. Recently, the application of high pressure in food preservation and processing has garnered new interest (Hayashi 1989; Balny et al, 1992). To collect precise kinetic data for pressure-induced degermination, we constructed a device which consisted of 10 pressure vessels that could be thermostated in two groups of five each. Each vessel had an inner diameter of 1.2cm and an inner length of 12 cm. The samples were separated from the pressure medium, water, by polyethylene tubes or bags. The maximum pressure was 7 kbar. The vegetative bacteria were always freshly cultured from one single organism before each experimental run. The preparations were allowed to grow to the exponential phase and were used in experiments just before the stationary phase had been reached.

A cohort study is one in which the outcome (usually disease status) is ascertained for groups of individuals defined on the basis of their exposure. At the time exposure status is determined, all must be free of the disease. All eligible participants are then followed up over time. Since exposure status is determined before the occurrence of the outcome, a cohort study can clarify the temporal sequence between exposure and outcome, with minimal information bias. The historical and the population cohort study (Box 9.1) are efficient variants of the classical cohort study described above, which nevertheless retain the essential components of the cohort study design. The exposure can be dichotomous [i.e. exposed (to obstetric complications at birth) vs. not exposed], or graded as degrees of exposure (e.g. no recent life events, one to two life events, three or more life events). The use of grades of exposure strengthens the results of a cohort study by supporting or refuting the hypothesis that the incidence of the disease increases with increasing exposure to the risk factor; a so-called dose–response relationship. The essential features of a cohort study are: ♦ participants are defined by their exposure status rather than by outcome (as in case–control design); ♦ it is a longitudinal design: exposure status must be ascertained before outcome is known. The classical cohort study In a classical cohort study participants are selected for study on the basis of a single exposure of interest. This might be exposure to a relatively rare occupational exposure, such as ionizing radiation (through working in the nuclear power industry). Care must be taken in selecting the unexposed cohort; perhaps those working in similar industries, but without any exposure to radiation. The outcome in this case might be leukaemia. All those in the exposed and unexposed cohorts would need to be free of leukaemia (hence ‘at risk’) on recruitment into the study. The two cohorts would then be followed up for (say) 10 years and rates at which they develop leukaemia compared directly. Classical cohort studies are rare in psychiatric epidemiology. This may be in part because this type of study is especially suited to occupational exposures, which have previously been relatively little studied as causes of mental illness. However, this may change as the high prevalence of mental disorders in the workplace and their negative impact upon productivity are increasingly recognized. The UK Gulf War Study could be taken as one rather unusual example of the genre (Unwin et al. 1999). Health outcomes, including mental health status, were compared between those who were deployed in the Persian Gulf War in 1990–91, those who were later deployed in Bosnia, and an ‘era control group’ who were serving at the time of the Gulf war but were not deployed. There are two main variations on this classical cohort study design: they are popular as they can, depending on circumstances, be more efficient than the classical cohort design. The population cohort study In the classical cohort study, participants are selected on the basis of exposure, and the hypothesis relates to the effect of this single exposure on a health outcome. However, a large cohort or panel of subjects are sometimes recruited and followed up, often over many years, to study multiple exposures and outcomes. No separate comparison group is required as the comparison group is generally an unexposed sub-group of the panel. Examples include the British Doctor's Study in which over 30,000 British doctors were followed up for over 20 years to study the effects of smoking and other exposures on health (Doll et al. 1994), and the Framingham Heart Study, in which residents of a town in Massachusetts, USA have been followed up for 50 years to study risk factors for coronary heart disease (Wolf et al. 1988). The Whitehall and Whitehall II studies in the UK (Fuhrer et al. 1999; Stansfeld et al. 2002) were based again on an occupationally defined cohort, and have led to important findings concerning workplace conditions and both physical and psychiatric morbidity. Birth cohort studies, in which everyone born within a certain chronological interval are recruited, are another example of this type of study. In birth cohorts, participants are commonly followed up at intervals of 5–10 years. Many recent panel studies in the UK and elsewhere have been funded on condition that investigators archive the data for public access, in order that the dataset might be more fully exploited by the wider academic community. Population cohort studies can test multiple hypotheses, and are far more common than any other type of cohort study. The scope of the study can readily be extended to include mental health outcomes. Thus, both the British Doctor's Study (Doll et al. 2000) and the Framingham Heart Study (Seshadri et al. 2002) have gone on to report on aetiological factors for dementia and Alzheimer's Disease as the cohorts passed into the age groups most at risk for these disorders. A variant of the population cohort study is one in which those who are prevalent cases of the outcome of interest at baseline are also followed up effectively as a separate cohort in order (a) to study the natural history of the disorder by estimating its maintenance (or recovery) rate, and (b) studying risk factors for maintenance (non-recovery) over the follow-up period (Prince et al. 1998). Historical cohort studies In the classical cohort study outcome is ascertained prospectively. Thus, new cases are ascertained over a follow-up period, after the exposure status has been determined. However, it is possible to ascertain both outcome and exposure retrospectively. This variant is referred to as a historical cohort study (Fig. 9.1). A good example is the work of David Barker in testing his low birth weight hypothesis (Barker et al. 1990; Hales et al. 1991). Barker hypothesized that risk for midlife vascular and endocrine disorders would be determined to some extent by the ‘programming’ of the hypothalamo-pituitary axis through foetal growth in utero. Thus ‘small for dates’ babies would have higher blood pressure levels in adult life, and greater risk for type II diabetes (through insulin resistance). A prospective cohort study would have recruited participants at birth, when exposure (birth weight) would be recorded. They would then be followed up over four or five decades to examine the effect of birth weight on the development of hypertension and type II diabetes. Barker took the more elegant (and feasible) approach of identifying hospitals in the UK where several decades previously birth records were meticulously recorded. He then traced the babies as adults (where they still lived in the same area) and measured directly their status with respect to outcome. The ‘prospective’ element of such studies is that exposure was recorded well before outcome even though both were ascertained retrospectively with respect to the timing of the study. The historical cohort study has also proved useful in psychiatric epidemiology where it has been used in particular to test the neurodevelopmental hypothesis for schizophrenia (Jones et al. 1994; Isohanni et al. 2001). Jones et al. studied associations between adult-onset schizophrenia and childhood sociodemographic, neurodevelopmental, cognitive, and behavioural factors in the UK 1946 birth cohort; 5362 people born in the week 3–9 March 1946, and followed up intermittently since then. Subsequent onsets of schizophrenia were identified in three ways: (a) routine data: cohort members were linked to the register of the Mental Health Enquiry for England in which mental health service contacts between 1974 and 1986 were recorded; (b) cohort data: hospital and GP contacts (and the reasons for these contacts) were routinely reported at the intermittent resurveys of the cohort; (c) all cohort participants identified as possible cases of schizophrenia were given a detailed clinical interview (Present State examination) at age 36. Milestones of motor development were reached later in cases than in non-cases, particularly walking. Cases also had more speech problems than had noncases. Low educational test scores at ages 8,11, and 15 years were a risk factor. A preference for solitary play at ages 4 and 6 years predicted schizophrenia. A health visitor's rating of the mother as having below average mothering skills and understanding of her child at age 4 years was a predictor of schizophrenia in that child. Jones concluded ‘differences between children destined to develop schizophrenia as adults and the general population were found across a range of developmental domains. As with some other adult illnesses, the origins of schizophrenia may be found in early life’. Jones' findings were largely confirmed in a very similar historical cohort study in Finland (Isohanni et al. 2001); a 31 year follow-up of the 1966 North Finland birth cohort (n = 12,058). Onsets of schizophrenia were ascertained from a national hospital discharge register. The ages at learning to stand, walk and become potty-trained were each related to subsequent incidence of schizophrenia and other psychoses. Earlier milestones reduced, and later milestones increased, the risk in a linear manner. These developmental effects were not seen for non-psychotic outcomes. The findings support hypotheses regarding psychosis as having a developmental dimension with precursors apparent in early life. There are many conveniences to this approach for the contemporary investigator. ♦ The exposure data has already been collected for you. ♦ The follow-up period has already elapsed. ♦ The design maintains the essential feature of the cohort study, namely that information bias with respect to the assessment of the exposure should not be a problem. ♦ As with the Barker hypothesis example, historical cohort studies are particularly useful for investigating associations across the life course, when there is a long latency between hypothesized exposure and outcome. Despite these important advantages, such retrospective studies are often limited by reliance on historical data that was collected routinely for other purposes; often these data will be inaccurate or incomplete. Also information about possible confounders, such as smoking or diet, may be inadequate.