Surrogacy and autonomy

Surrogacy contracts pose a sufficiently great number of serious risks to personal autonomy to justify their impermissability. These risks, such as the surrogate mother's loss of control over her body and daily activities during the pregnancy, the powerlessness of having to give up a child to whom one may have formed a deep attachment, and the normal dangers of pregnancy, seriously undercut the ability to make a fully informed and free choice to become a surrogate mother. The social circumstances of surrogate mothers and the prerequisites of dispositional autonomy are analyzed, as is the attitude toward women fostered by such contracts, their effect on the child involved, and their harmful view of children as property.     

Hyperbolastic growth models: theory and application

Background  

Mathematical models describing growth kinetics are very important for predicting many biological phenomena such as tumor volume, speed of disease progression, and determination of an optimal radiation and/or chemotherapy schedule. Growth models such as logistic, Gompertz, Richards, and Weibull have been extensively studied and applied to a wide range of medical and biological studies. We introduce a class of three and four parameter models called "hyperbolastic models" for accurately predicting and analyzing self-limited growth behavior that occurs e.g. in tumors. To illustrate the application and utility of these models and to gain a more complete understanding of them, we apply them to two sets of data considered in previously published literature.     

Island chain models and gradient systems

A range of island chain models in the literature are gradient systems. This implies that the asymptotic dynamics of such models is trivial: all solutions tend to stationary points. Results for one-dimensional island chains are extended to habitats with more complicated geometries and to models with competitive species.     

Mathematical models of endocrine systems

There is proposed a generalized mathematical model of endocrine systems, consisting of a set of differential equations which describe a chain of chemical reactions. The product of each reaction stimulates or inhibits some other reaction in the chain except possibly the last, which may or may not influence the system. At least one reaction must be independent and able to proceed without stimulation or inhibition by the products of other reactions. If only two reactions of the type assumed constitute a closed chain, sustained periodic variations in the concentrations of the reaction products cannot occur. If the chain consists of three or more reactions forming a closed loop, sustained oscillations, such as are observed in the menstrual cycle or in the mental disorder called periodic catatonia, can occur under suitable conditions. In this case, the concentrations of the system components exhibit relaxation oscillations characterized by periodic degeneration of the system when an independent reaction becomes completely inhibited by other reaction products. A set of conditions sufficient to produce periodicities in component concentrations is presented. Application of the model to the normally periodic system of the menstrual cycle and to the abnormal endocrine system which causes periodic catatonia is discussed.     

Dynamic causal models and autopoietic systems

Dynamic Causal Modelling (DCM) and the theory of autopoietic systems are two important conceptual frameworks. In this review, we suggest that they can be combined to answer important questions about self-organising systems like the brain. DCM has been developed recently by the neuroimaging community to explain, using biophysical models, the non-invasive brain imaging data are caused by neural processes. It allows one to ask mechanistic questions about the implementation of cerebral processes. In DCM the parameters of biophysical models are estimated from measured data and the evidence for each model is evaluated. This enables one to test different functional hypotheses (i.e., models) for a given data set. Autopoiesis and related formal theories of biological systems as autonomous machines represent a body of concepts with many successful applications. However, autopoiesis has remained largely theoretical and has not penetrated the empiricism of cognitive neuroscience. In this review, we try to show the connections that exist between DCM and autopoiesis. In particular, we propose a simple modification to standard formulations of DCM that includes autonomous processes. The idea is to exploit the machinery of the system identification of DCMs in neuroimaging to test the face validity of the autopoietic theory applied to neural subsystems. We illustrate the theoretical concepts and their implications for interpreting electroencephalographic signals acquired during amygdala stimulation in an epileptic patient. The results suggest that DCM represents a relevant biophysical approach to brain functional organisation, with a potential that is yet to be fully evaluated.     

Fuzzy systems vegetation theory

Fuzzy systems vegetation theory is a comprehensive framework for the expression of vegetation theory and conceptual models, as well as the development of vegetation analyses. It is applicable to vegetation/environment relations, vegetation dynamics, and the effects of environmental dynamics on vegetation composition. Fuzzy systems vegetation theory is a fuzzy set generalization of dynamical systems theory and incorporates a formal logic and mathematics. This paper presents the elements of fuzzy systems vegetation theory and discusses the relationship of the fuzzy systems theory to the geometric concepts generally employed in vegetation theory.     

Computational models in systems biology

A report of the 6th International Conference on Computational Methods in Systems Biology, Rostock, Germany, 12-15 October 2008.One of the chief goals of systems biology is to build mechanistic mathematical models of biological systems to further the understanding of biological detail. Such models often aim at predicting the outcome of potentially interesting biological experiments, and if such predictions are confirmed by wet-lab observations, an important step forward is made. How exactly such models are constructed and how predictions are computed were at the core of a recent conference on Computational Methods in Systems Biology that brought 80 participants to Rostock, Germany (for conference proceedings see volume 5307 of Lecture Notes in Bioinformatics http://dx.doi.org/10.1007/978-3-540-88562-7).A simplistic approach to model construction might be to capture everything that is known about a system and simulate it in supercomputers. While this is appropriate for some systems, it is impossible or highly impracticable for many others. This is mostly due to the complexity of biological systems, which demand simplification to make them amenable to modeling. Such simplifications have to capture the essence of the processes of interest, while neglecting as many of the less important details as possible. Thus, one can consider model building in systems biology as the art of building caricatures of life: capture the essence, ignore the rest.     

Computational models in systems biology

A report of the 6th International Conference on Computational Methods in Systems Biology, Rostock, Germany, 12-15 October 2008.     

The theory of functional systems and purposeful behavior

The role of probability forecasting in the purposive behavior under conditions of subjective uncertainty is considered in terms of the theory of functional systems. Participation of the probability forecasting in the afferent synthesis, goal formation, formation of the acceptor of action result and action program, and, finally, in the action program actualization is substantiated. The model of behavior under conditions of subjective uncertainty is advanced. It includes all the classical elements of the model of behavioral act developed by P.K. Anokhin. In order to take into account the probability aspects of behavior, the role of probability forecasting is emphasized at every stage of the system functioning. In addition to the classical elements, two novel components are introduced. These are the "memory buffer" (results of searching reactions) and the apparatus of probability decisions about changes in the action program. By the memory buffer an apparatus is meant, which gathers and stores the information about the results of many behavioral acts performed during the actualization of the action program. This information is used in the process of making a probability decision as whether to alter or not the action program after each specific behavioral act. Such an approach integrates the probability forecasting and the theory of functional systems. The theory becomes universal, i.e., applicable not only to deterministic but also to probabilistic environments.     

Biostructural theory of the living systems

Eugen Macovschi is among the few scientists who tried, and partly succeeded, to explain the differences between "dead" and "living" in biological sciences. He discovered and characterized the so-called biostructure of the living bodies and worked out a biostructural theory, which is the first supramolecular conception in biology. Nevertheless, complex biological systems are currently considered only from the molecular point of view, although they may be regarded as specific phenomena on highly structured bodies within the four-dimensional Universe. According to Macovschi, the biostructure provides organisms with life properties and controls their life processes and chemical changes. Nevertheless, plant cells or bacterial ones differ much from the animal or human cells. In fact, there are various biostructures which are related with cell properties. Hence, this theory creates confusions and cannot be easily used to explain all the properties of the biosystems. Consequently, it is our goal to highlight the principles, advantages, limitations, and applications of the biostructural theory, which might support new ideas and theories in modern life sciences.     

A complex systems theory of teleology

Part I [sections 2–4] draws out the conceptual links between modern conceptions of teleology and their Aristotelian predecessor, briefly outlines the mode of functional analysis employed to explicate teleology, and develops the notion of cybernetic organisation in order to distinguish teleonomic and teleomatic systems. Part II is concerned with arriving at a coherent notion of intentional control. Section 5 argues that intentionality is to be understood in terms of the representational properties of cybernetic systems. Following from this, section 6 argues that intentional control needs to be seen as a particular type of relationship between the system and its environment.I would like to gratefully acknowledge the large guiding input of Professor C. A. Hooker, who supervised the development of this paper from its inception. Bill herfel also provided valuable criticism of late drafts.     

Thermostability of membrane systems in organic solvents

Two multisubunit enzymes of the inner mitochondrial membrane, cytochrome oxidase and the H+-ATPase may be transferred into highly apolar solvents as protein-lipid complexes. At 70 degrees C and an initial water concentration of 13 microliters per ml organic solvent (toluene), the half-life of the ATPase was approx. 11 h, whereas that of cytochrome oxidase was about 100 s. Thermostability of cytochrome oxidase could be increased more than 100-times by decreasing the water concentration to 3 microliters per ml toluene. At this latter concentration of water the half-life of the ATPase at 90, 80 and 70 degrees C was 5, 48 and 96 h, respectively.     

A relational theory of biological systems

The relational phenomena exhibited by metabolizing systems may be considered as special cases of those exhibited by a more general class of systems. This class is specified, and some of tis properties developed. An attempt is then made to apply these properties to a theory of metabolism by suitable specialization. A number of biologically significant theorems are obtained which apply directly to the theory of the free-living single cell. Among the results obtained are the following: On the basis of our model, there must always exist a component of the system which cannot be replaced or repaired by the system in the event of its inhibition or destruction. Under certain conditions, a metabolizing system possesses a component the inhibition of which will completely terminate the metabolic activity of the system. Furthermore a number of other diverse phenomena, such as the effects of a deficient environment, encystment phenomena, and even an indication of why a metabolizing system which represents a cell should possess a nucleus, follow in a straightforward fashion from our model.     

Divergent controls of soil organic carbon between observations and process-based models

Biogeochemistry - The storage and cycling of soil organic carbon (SOC) are governed by multiple co-varying factors, including climate, plant productivity, edaphic properties, and disturbance...