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Physiological Components (physiological + component)
Selected AbstractsA 5-Year Prospective Evaluation of DSM-IV Alcohol Dependence With and Without a Physiological ComponentALCOHOLISM, Issue 5 2003M. A. Schuckit Background: The DSM-III-R removed tolerance and withdrawal as required elements for a diagnosis of alcohol dependence. Although this practice was continued in DSM-IV, the more recent manual asked clinicians to note whether physiological aspects of withdrawal (tolerance and withdrawal) had ever been experienced. Few studies have determined the prognostic meaning of a history of a physiological component to DSM-IV alcohol dependence. Methods: Face-to-face structured interviews were used to evaluate the course of alcohol, drug, and psychiatric problems during the subsequent 5 years for 1094 alcohol-dependent men and women. These subjects had been classified into subgroups at the time of initial interview regarding evidence of tolerance or withdrawal, and all evaluations were based on DSM-IV criteria. At baseline, the application of DSM-IV diagnostic guidelines resulted in 649 (59.3%) individuals having a history of an alcohol withdrawal syndrome, with or without tolerance (group 1); 391 (35.7%) with histories of tolerance but not withdrawal (group 2); and 54 (4.9%) with no lifetime histories of tolerance or withdrawal (group 3). Results: During the 5-year follow-up, both the broad (group 1 plus 2 versus group 3) and narrow (group 1 versus group 2 plus group 3) definitions of physiological dependence were associated with more alcohol and drug problems. However, for most items, this differential primarily reflected differences between groups 1 and 3, with a less impressive effect by group 2. Although no group differences were noted for the rate of independent major depressive episodes, substance-induced depressions did differentiate among groups, a finding also most closely related to the distinction between groups 1 and 3. Conclusions: These data support the prognostic importance of noting the presence of a physiological component in alcohol dependence and indicate the potential relevance of limiting the definition of a physiological component to withdrawal. [source] What are the effects of nitrogen deficiency on growth components of lettuce?NEW PHYTOLOGIST, Issue 3 2000M. R. BROADLEY Relationships between nitrogen (N) content and growth are routinely measured in plants. This study determined the effects of N on the separate morphological and physiological components of plant growth, to assess how N-limited growth is effected through these components. Lettuce (Lactuca sativa) plants were grown hydroponically under contrasting N-supply regimes, with the external N supply either maintained continuously throughout the period of study, or withdrawn for up to 14 d. Richards' growth functions, selected using an objective curve-fitting technique, accounted for 99.0 and 99.1% of the variation in plant dry weight for control and N-limited plants respectively. Sublinear relationships occurred between N and relative growth rates under restricted N-supply conditions, consistent with previous observations. There were effects of treatment on morphological and physiological components of growth. Leaf weight ratio increased over time in control plants and decreased in N- limited plants. Shoot:root ratio followed a similar pattern. On a whole-plant basis, assimilation of carbon decreased in N-limited plants, a response paralleled by differences in stomatal conductance between treatments. Changes in C assimilation, expressed as a function of stomatal conductance to water vapour, suggest that the effects of N limitation on growth did not result directly from a lack of photosynthetic enzymes. Relationships between plant N content and components of growth will depend on the availability of different N pools for remobilization and use within the plant. [source] Characteristic changes in the physiological components of cybersicknessPSYCHOPHYSIOLOGY, Issue 5 2005Young Youn Kim Abstract We investigated the characteristic changes in the physiology of cybersickness when subjects were exposed to virtual reality. Sixty-one participants experienced a virtual navigation for a total of 9.5 min, and were required to detect specific virtual objects. Three questionnaires for sickness susceptibility and immersive tendency were obtained before the navigation. Sixteen electrophysiological signals were recorded before, during, and after the navigation. The severity of cybersickness experienced by participants was reported from a simulator sickness questionnaire after the navigation. The total severity of cybersickness had a significant positive correlation with gastric tachyarrhythmia, eyeblink rate, heart period, and EEG delta wave and a negative correlation with EEG beta wave. These results suggest that cybersickness accompanies the pattern changes in the activities of the central and the autonomic nervous systems. [source] Incorporating Physiological and Biochemical Mechanisms into Pharmacokinetic,Pharmacodynamic Models: A Conceptual Framework,BASIC AND CLINICAL PHARMACOLOGY & TOXICOLOGY, Issue 1 2010Svein G. Dahl In general, modelling of data has the purpose (1) to describe experimental data, (2a) to reduce the amount of data resulting from an experiment, e.g. a clinical trial and (2b) to obtain the most relevant parameters, (3) to test hypotheses and (4) to make predictions within the boundaries of experimental conditions, e.g. range of doses tested (interpolation) and out of the boundaries of the experimental conditions, e.g. to extrapolate from animal data to the situation in man. Describing the drug/xenobiotic-target interaction and the chain of biological events following the interaction is the first step to build a biologically based model. This is an approach to represent the underlying biological mechanisms in qualitative and also quantitative terms, thus being inherently connected in many aspects to systems biology. As the systems biology models may contain variables in the order of hundreds connected with differential equations, it is obvious that it is in most cases not possible to assign values to the variables resulting from experimental data. Reduction techniques may be used to create a manageable model which, however, captures the biologically meaningful events in qualitative and quantitative terms. Until now, some success has been obtained by applying empirical pharmacokinetic/pharmacodynamic models which describe direct and indirect relationships between the xenobiotic molecule and the effect, including tolerance. Some of the models may have physiological components built in the structure of the model and use parameter estimates from published data. In recent years, some progress toward semi-mechanistic models has been made, examples being chemotherapy-induced myelosuppression and glucose-endogenous insulin-antidiabetic drug interactions. We see a way forward by employing approaches to bridge the gap between systems biology and physiologically based kinetic and dynamic models. To be useful for decision making, the ,bridging' model should have a well founded mechanistic basis, but being reduced to the extent that its parameters can be deduced from experimental data, however capturing the biological/clinical essential details so that meaningful predictions and extrapolations can be made. [source] Bioengineering nitrogen acquisition in rice: can novel initiatives in rice genomics and physiology contribute to global food security?BIOESSAYS, Issue 6 2004Dev T. Britto Rice is the most important crop species on earth, providing staple food for 70% of the world's human population. Over the past four decades, successes in classical breeding, fertilization, pest control, irrigation and expansion of arable land have massively increased global rice production, enabling crop scientists and farmers to stave off anticipated famines. If current projections for human population growth are correct, however, present rice yields will be insufficient within a few years. Rice yields will have to increase by an estimated 60% in the next 30 years, or global food security will be in danger. The classical methods of previous green revolutions alone will probably not be able to meet this challenge, without being coupled to recombinant DNA technology. Here, we focus on the promise of these modern technologies in the area of nitrogen acquisition in rice, recognizing that nitrogen deficiency compromises the realization of rice yield potential in the field more than any other single factor. We summarize rice-specific advances in four key areas of research: (1) nitrogen fixation, (2) primary nitrogen acquisition, (3) manipulations of internal nitrogen metabolism, and (4) interactions between nitrogen and photosynthesis. We develop a model for future plant breeding possibilities, pointing out the importance of coming to terms with the complex interactions among the physiological components under manipulation, in the context of ensuring proper targeting of intellectual and financial resources in this crucial area of research. BioEssays 26:683,692, 2004. © 2004 Wiley Periodicals, Inc. [source] | |||||||||||||