(1/235) Falsification of matching theory: changes in the asymptote of Herrnstein's hyperbola as a function of water deprivation.
Five rats pressed levers on variable-interval schedules of water reinforcement at various levels of water deprivation. In one phase of the experiment, three deprivation conditions that replicated conditions in Heyman and Monaghan (1987) were arranged, along with three less extreme deprivation conditions. In a second phase, water deprivation was arranged so that subjects were exposed to a greater range of access to water per day. Herrnstein's hyperbola described the rats' response-rate data well. The y asymptote, k, of the hyperbola appeared roughly constant over the conditions that replicated those of Heyman and Monaghan, but decreased markedly when less extreme deprivation conditions were included. In addition, k varied systematically when the second method of arranging deprivation was used. These results falsify a strong form of matching theory and confirm predictions made by linear system theory. (+info)
(2/235) Anatomic genomics: systems of genes supporting the biology of systems.
This essay lays the groundwork for the concept that "anatomy" in the new millennium will be a subject that is increasingly based on understanding the parallel relationships between systems of genes on chromosomes and the structures defined by these genes. The concept of Anatomic Genomics is introduced in terms of systems of genes on chromosomes, which actually mirror the biology of anatomically defined systems. A case is made for the possibility that genomes may be structured in ways that make local but not necessarily global sense. In the new millennium, systems biologists have the opportunity to be the creators and purveyors of this new anatomy. (+info)
(3/235) Systems biology: the reincarnation of systems theory applied in biology?
With the availability of quantitative data on the transcriptome and proteome level, there is an increasing interest in formal mathematical models of gene expression and regulation. International conferences, research institutes and research groups concerned with systems biology have appeared in recent years and systems theory, the study of organisation and behaviour per se, is indeed a natural conceptual framework for such a task. This is, however, not the first time that systems theory has been applied in modelling cellular processes. Notably in the 1960s systems theory and biology enjoyed considerable interest among eminent scientists, mathematicians and engineers. Why did these early attempts vanish from research agendas? Here we shall review the domain of systems theory, its application to biology and the lessons that can be learned from the work of Robert Rosen. Rosen emerged from the early developments in the 1960s as a main critic but also developed a new alternative perspective to living systems, a concept that deserves a fresh look in the post-genome era of bioinformatics. (+info)
(4/235) Temperature effects on energy metabolism: a dynamic system analysis.
Q(10) factors are widely used as indicators of the magnitude of temperature-induced changes in physico-chemical and physiological rates. However, there is a long-standing debate concerning the extent to which Q(10) values can be used to derive conclusions about energy metabolism regulatory control. The main point of this disagreement is whether or not it is fair to use concepts derived from molecular theory in the integrative physiological responses of living organisms. We address this debate using a dynamic systems theory, and analyse the behaviour of a model at the organismal level. It is shown that typical Q(10) values cannot be used unambiguously to deduce metabolic rate regulatory control. Analytical constraints emerge due to the more formal and precise equation used to compute Q(10), derived from a reference system composed from the metabolic rate and the Q(10). Such an equation has more than one unknown variable and thus is unsolvable. This problem disappears only if the Q(10) is assumed to be a known parameter. Therefore, it is concluded that typical Q(10) calculations are inappropriate for addressing questions about the regulatory control of a metabolism unless the Q(10) values are considered to be true parameters whose values are known beforehand. We offer mathematical tools to analyse the regulatory control of a metabolism for those who are willing to accept such an assumption. (+info)
(5/235) Family systems practice in pediatric psychology.
OBJECTIVE: To present a pediatric psychology consultation treatment framework based on family systems and developmental theories. METHODS: After reviewing background relevant to family systems interventions, a five-step protocol (referral, assessment, collaboration, outcome) for consultation is presented, using case examples from our pediatric oncology service, to illustrate joining, focusing, promoting competence and collaboration with patients, families, and staff. RESULTS: Using protocols based on family systems frameworks, pediatric psychologists can offer systems-oriented consultation to patients, families, and healthcare teams. CONCLUSIONS: Further development and evaluation of family systems protocols are necessary to understand the efficacy of these approaches and their role in training and practice. (+info)
(6/235) Hierarchical organization of modularity in metabolic networks.
Spatially or chemically isolated functional modules composed of several cellular components and carrying discrete functions are considered fundamental building blocks of cellular organization, but their presence in highly integrated biochemical networks lacks quantitative support. Here, we show that the metabolic networks of 43 distinct organisms are organized into many small, highly connected topologic modules that combine in a hierarchical manner into larger, less cohesive units, with their number and degree of clustering following a power law. Within Escherichia coli, the uncovered hierarchical modularity closely overlaps with known metabolic functions. The identified network architecture may be generic to system-level cellular organization. (+info)
(7/235) Origin of multicellular organisms as an inevitable consequence of dynamical systems.
The origin of multicellular organisms is studied by considering a cell system that satisfies minimal conditions, that is, a system of interacting cells with intracellular biochemical dynamics, and potentiality in reproduction. Three basic features in multicellular organisms-cellular diversification, robust developmental process, and emergence of germ-line cells-are found to be general properties of such a system. Irrespective of the details of the model, such features appear when there are complex oscillatory dynamics of intracellular chemical concentrations. Cells differentiate from totipotent stem cells into other cell types due to instability in the intracellular dynamics with cell-cell interactions, as explained by our isologous diversification theory (Furusawa and Kaneko, 1998a; Kaneko and Yomo, 1997). This developmental process is shown to be stable with respect to perturbations, such as molecular fluctuations and removal of some cells. By further imposing an adequate cell-type-dependent adhesion force, some cells are released, from which the next generation cell colony is formed, and a multicellular organism life-cycle emerges without any finely tuned mechanisms. This recursive production of multicellular units is stabilized if released cells are few in number, implying the separation of germ cell lines. Furthermore, such an organism with a variety of cellular states and robust development is found to maintain a larger growth speed as an ensemble by achieving a cooperative use of resources, compared to simple cells without differentiation. Our results suggest that the emergence of multicellular organisms is not a "difficult problem" in evolution, but rather is a natural consequence of a cell colony that can grow continuously. (+info)
(8/235) Stoichiometric network theory for nonequilibrium biochemical systems.
We introduce the basic concepts and develop a theory for nonequilibrium steady-state biochemical systems applicable to analyzing large-scale complex isothermal reaction networks. In terms of the stoichiometric matrix, we demonstrate both Kirchhoff's flux law sigma(l)J(l)=0 over a biochemical species, and potential law sigma(l) mu(l)=0 over a reaction loop. They reflect mass and energy conservation, respectively. For each reaction, its steady-state flux J can be decomposed into forward and backward one-way fluxes J = J+ - J-, with chemical potential difference deltamu = RT ln(J-/J+). The product -Jdeltamu gives the isothermal heat dissipation rate, which is necessarily non-negative according to the second law of thermodynamics. The stoichiometric network theory (SNT) embodies all of the relevant fundamental physics. Knowing J and deltamu of a biochemical reaction, a conductance can be computed which directly reflects the level of gene expression for the particular enzyme. For sufficiently small flux a linear relationship between J and deltamu can be established as the linear flux-force relation in irreversible thermodynamics, analogous to Ohm's law in electrical circuits. (+info)