Evolution in fine-grained environments I. Environmental runs and the evolution of homeostasis

In this paper we discuss the problem of evolution when individual organisms are subjected to heterogeneous environments within their own lifetimes. We first develop a model of environmental heterogeneity in which there are two discrete environmental states. Transitions between states are governed by a stochastic matrix. Next, we examine how an organism responds to this heterogeneity. We assume that L consecutive time units of the environmental process are sampled during the normal life span of the organism, and that the individual's fitness is determined in part by a component unrelated to this heterogeneity and by other components that describe the fitness response to the heterogeneity. The fitness responses are functions of the environmental state and of how long the organism has been previously exposed to that state; i.e., fitness response is dependent upon the environmental context. We then discuss how this individually experienced heterogeneity is translated to the populational level. Finally, genetic constraints are overlaid so that the tools of population genetics may be used to make evolutionary predictions.     

Deleterious Mutations and the Origin of the Meiotic Ploidy Cycle

A population genetical model is investigated in which the organism either alternates between diploid and haploid states or lives entirely in the haploid state. The behavior of the organism is determined by the genotype at a modifier locus. At an independent locus deleterious mutations occur at a low but constant frequency. It is found that the haploid behavior is always an evolutionarily attainable stable trait, while the ploidy-cyclic behavior is an evolutionarily attainable stable trait only when a certain condition holds. This condition depends on the strength of selection, the degree of "sheltering" given by the heterozygote state, and the degree of linkage between the modifier locus and the locus under selection. The last result leads to the speculation that the eukaryotes are derived from an organism which first developed more than one chromosome before it evolved the ploidy cycle.     

Criteria for the determination of the direction of character state changes

Phylogenetic reconstructions cannot be adequately assessed except in terms of probability models which represent the processes of change. An tionary tree model of bifurcating splits, together with a Brownian motion model of genetic drift have been shown to allow successful reconstruction of phylogeny from data relating to gene frequencies of blood groups from human populations. Changes in state cannot be dealt with by the Brownian motion model, and no adequate models have been proposed for character state changes from the many possible sources. So, while the tionary tree model is applicable to these problems too, only heuristic methods of analysis of the state data are available, and these are known to be unsatisfactory under certain conditions. The concepts of homology, polarity and homoplasy have been developed out of the attempt to describe the nature of morphological state data, which is unpredictably related to genetic state data. The experimental study of comparative functional morphology, at any developmental stage of an organism, is considered to be the only valid tool for investigating the resulting character state tree hypothesis. However, the speculative nature of such investigations is admitted.     

A new mathematical model of the dynamics of an age cohort population

A new generalized conception of an organism is given. Based on this conception, a new mathematical model of ontogenesis of an individual and the survival of the age cohort of population was proposed. By using real data on the dynamics of the survival of the age cohort of population, the model enables one to determine the parameters characterizing the relationship man-environment in the context of survival and calculate the dynamics (from birth to death) of the model variables of the state of the organism.     

Molecular signaling involved in regulating feeding and other mitivated behaviors

The metabolic and nutritional status of an organism influences multiple behaviors in addition to food intake. When an organism is hungry, it employs behaviors that help it locate and ingest food while suppressing behaviors that are not associated with this goal. Alternatively, when an organism is satiated, food-seeking behaviors are repressed so that the animal can direct itself to other goal-oriented tasks such as reproductive behaviors. Studies in both vertebrate and invertebrate model systems have revealed that food-deprived and -satiated behaviors are differentially executed and integrated via common molecular signaling mechanisms. This article discusses cellular and molecular mechanisms for how insulin, neuropeptide Y (NPY), and serotonin utilize common signaling pathways to integrate feeding and metabolic state with other motivated behaviors. Insulin, NPY, and serotonin are three of the most well-studied molecules implicated in regulating such behaviors. Overall, insulin signaling allows an organism to coordinate proper behavioral output with changes in metabolism, NPY activates behaviors required for locating and ingesting food, and serotonin modulates behaviors performed when an organism is satiated. These three molecules work to ensure that the proper behaviors are executed in response to the feeding state of an organism. These authors contributed equally to this work.     

Molecular signaling involved in regulating feeding and other motivated behaviors

The metabolic and nutritional status of an organism influences multiple behaviors in addition to food intake. When an organism is hungry, it employs behaviors that help it locate and ingest food while suppressing behaviors that are not associated with this goal. Alternatively, when an organism is satiated, food-seeking behaviors are repressed so that the animal can direct itself to other goal-oriented tasks such as reproductive behaviors. Studies in both vertebrate and invertebrate model systems have revealed that food-deprived and -satiated behaviors are differentially executed and integrated via common molecular signaling mechanisms. This article discusses cellular and molecular mechanisms for how insulin, neuropeptide Y (NPY), and serotonin utilize common signaling pathways to integrate feeding and metabolic state with other motivated behaviors. Insulin, NPY, and serotonin are three of the most well-studied molecules implicated in regulating such behaviors. Overall, insulin signaling allows an organism to coordinate proper behavioral output with changes in metabolism, NPY activates behaviors required for locating and ingesting food, and serotonin modulates behaviors performed when an organism is satiated. These three molecules work to ensure that the proper behaviors are executed in response to the feeding state of an organism.     

Changes in membrane fatty acid composition during entry of Vibrio vulnificus into the viable but nonculturable state

Vibrio vulnificus, a Gram-negative bacterium found in estuarine waters, is responsible for over 95% of all seafood-related deaths in the United States. As a result of a temperature downshift to 5 degrees C, this organism enters the viable but nonculturable (VBNC) state. Changes in the membrane fatty acid (FA) composition of V. vulnificus may be a contributing factor to the ability of this organism to enter into and survive in the VBNC state. This hypothesis was tested by incubating the organism at 5 degrees C in artificial sea water and analyzing the cells' FAs during the initial hours of temperature and nutrient down-shift. Prior to downshift, the predominant FAs were 16:0, 16:1 and 18:0. During the first four hours of downshift, statistically significant changes occurred in 15:0, 16:1, 16:0, 17:0, and 18:0. These results indicate that changes in FA composition occur prior to entry of V. vulnificus into the VBNC state, suggesting that the ability to maintain membrane fluidity may be a factor in this physiological response. Cells in which fatty acid synthesis was inhibited did not survive, indicating that active fatty acid metabolism is essential for entry of cells into the VBNC state.     

Complex sensory-motor sequence learning based on recurrent state representation and reinforcement learning

 A novel neural network model is presented that learns by trial-and-error to reproduce complex sensory-motor sequences. One subnetwork, corresponding to the prefrontal cortex (PFC), is responsible for generating unique patterns of activity that represent the continuous state of sequence execution. A second subnetwork, corresponding to the striatum, associates these state-encoding patterns with the correct response at each point in the sequence execution. From a neuroscience perspective, the model is based on the known cortical and subcortical anatomy of the primate oculomotor system. From a theoretical perspective, the architecture is similar to that of a finite automaton in which outputs and state transitions are generated as a function of inputs and the current state. Simulation results for complex sequence reproduction and sequence discrimination are presented. Received: 21 July 1994/Accepted in revised form: 21 March 1995     

The Benefits of Mutualism: A Conceptual Framework

There are three general mechanisms by which phenotypic benefits are transferred between unrelated organisms. First, one organism may purloin benefits from another by preying on or parasitizing the other organism. Second, one organism may enjoy benefits that are incidental to or a by-product of the self-serving traits of another organism. Third, an organism may invest in another organism if that investment produces return benefits which outweigh the cost of the investment. Interactions in which both parties gain a net benefit are mutualistic. The three mechanisms by which benefits are transferred between organisms can be combined in pairs to produce six possible kinds of original or 'basal' mutualisms that can arise from an amutualistic state. A review of the literature suggests that most or all interspecific mutualism have origins in three of the six possible kinds of basal mutualism. Each of these three basal mutualisms have byproduct benefits flowing in at least one direction. The transfer of by-product benefits and investment are common to both intra- and interspecific mutualisms, so that some interspecific mutualisms have intraspecific analogs. A basal mutualism may evolve to the point where each party invests in the other, sometimes obscuring the nature of the original interaction along the way. Two prominent models for the evolution of mutualism do not include by-product benefits: Roughgarden's model for the evolution of the damsel-fish anemone mutualism and the 'Tit-for-Tat' model of reciprocity. Using the conceptual framework presented here, including in particular by-product benefits, I have shown how it is possible to construct more parsimonious alternatives to both models.     

Application of a generalized MWC model for the mathematical simulation of metabolic pathways regulated by allosteric enzymes

In our effort to elucidate the systems biology of the model organism, Escherichia coli, we have developed a mathematical model that simulates the allosteric regulation for threonine biosynthesis pathway starting from aspartate. To achieve this goal, we used kMech, a Cellerator language extension that describes enzyme mechanisms for the mathematical modeling of metabolic pathways. These mechanisms are converted by Cellerator into ordinary differential equations (ODEs) solvable by Mathematica. In this paper, we describe a more flexible model in Cellerator, which generalizes the Monod, Wyman, Changeux (MWC) model for enzyme allosteric regulation to allow for multiple substrate, activator and inhibitor binding sites. Furthermore, we have developed a model that describes the behavior of the bifunctional allosteric enzyme aspartate kinase I-homoserine dehydrogenase I (AKI-HDHI). This model predicts the partition of enzyme activities in the steady state which paves the way for a more generalized prediction of the behavior of bifunctional enzymes.     

Use of body-water content to assess the physiological state of roach Rutilus rutilus L. in natural conditions

It is shown that in natural conditions roach have two levels of water content in their organisms during their annual cycle which reflect different physiological states of the fish. During the feeding period, the body-water content is maintained at a low level of 72.6 ± 0.05%, determining the physiological state related to the growth of fishes. In winter, spring, and postspawning periods, the water content in the roach organism is high, 75 ± 0.06%, which reflects the physiological state of survival during periods of the year unfavorable for growth. The water content in the organism of fish is a convenient integrated parameter for assessing the general physiological state of fish in natural conditions.     

缺血引起沙土鼠纹状体DARPP—32磷酸化状态的变化

采用蒙古沙土双侧颈总动脉阻断前脑缺血模型,以放射自显影（反向磷酸化,back-phosphorylation)及免疫印迹（Western blotting)法体外测定缺血时纹状体DARPP－32磷酸化水平和蛋白含量的变化,结果表明,短暂性缺血纹状体DARPP－32的免疫学活性和蛋白含量地明显改变。在缺血10min内,随缺血时间的延长,体外DARPP－32的[^32P]的掺入量在缺血5min时升高,在缺血2,7,10min时均降低,而反向磷酸化的测定结果表明体内DARPP－32磷酸化水平增高,说明缺血可诱导DARPP－32磷酸化水平变化。     

The logical structure of irreversible systems transformations: A theorem concerning Dollo's law and chaotic movement

The argument of historical irrevocability as an explanation for the irreversibility of organismic evolution is reconsidered. It is examined under which conditions a chain of transformations never can lead to a state equivalent to a previous one. It is shown to be sufficient to take into consideration that the environment of an organ also consists of the other organs in an organism. Under this prerequisite it is impossible to reach an ancestral state once more. This type of irreversibility depends solely on the mutual interdependency of characters within one organism. No reference to statistical arguments is necessary. The relationship between chaotic dynamic systems and the present theory is discussed.     

Changes in the activity of enzymes of renin-angiotensin and kinin systems in the rat brain after adrenalectomy and administration of hydrocortisone

It is shown that the activity of enzymes participating in renin-angiotensin and brain kinin systems' metabolism depends on functional state of hypothalamo-pituitary-adrenocortical system. Under experimental hypocorticism the activity of angiotensin-converting enzyme and kininase I in the hypothalamus, hippocamp, corpus striatum and rat pituitary decreases; the renin-like enzyme activity decreases in the corpus striatum but increases in the hypothalamus and hippocamp. After hydrocortisone administration to adrenalectomized rats the angiotensin-converting enzyme activity of the hippocamp and pituitary is shown to be normalized as well as renin-like enzyme and kininase I of the hippocamp and corpus striatum. The activity of the studied enzymes in the hypothalamus decreases in this case.     

Kinetic studies of the lactic acid fermentation in batch and continuous cultures

The fermentation kinetics of the homofermentative organism Lactobacillus delbrueckii in a glucose-yeast extract medium is studied in both batch and continuous culture under conditions of controlled pH. From a graphical analysis of the batch data, a mathematical model of the process is derived which relates bacterial growth, glucose utilization, and lactic acid formation. The parameters in the model represent the activity of the organism and are a function of pH, having a maximum value at about 5.90. In a continuous stirred tank fermentor (CSTF), the effect of pH, feed concentration, and residence time is observed. The feed medium is a constant ratio of two parts glucose to one part yeast extract plus added mineral salts. An approximate prediction of the steady-state behavior of the CSTF can be made using a method based on the kinetic model derived for the batch case. In making step changes from one steady state to another, the transient response is observed. Using the kinetic model to simulate the transient period, the calculated behavior qualitatively predicts the observed response.     

Extension of the biotic ligand model of acute toxicity to a physiologically-based model of the survival time of rainbow trout (Oncorhynchus mykiss) exposed to silver

Chemical speciation controls the bioavailability and toxicity of metals in aquatic systems and regulatory agencies are recognizing this as they develop updated water quality criteria (WQC) for metals. The factors that affect bioavailability may be quantitatively evaluated with the biotic ligand model (BLM). Within the context of the BLM framework, the 'biotic ligand' is the site where metal binding results in the manifestation of a toxic effect. While the BLM does account for the speciation and complexation of dissolved metal in solution, and competition among the free metal ion and other cations for binding sites at the biotic ligand, it does not explicitly consider either the physiological effects of metals on aquatic organisms, or the direct effect of water chemistry parameters such as pH, Ca(2+)and Na(+) on the physiological state of the organism. Here, a physiologically-based model of survival time is described. In addition to incorporating the effects of water chemistry on metal availability to the organism, via the BLM, it also considers the interaction of water chemistry on the physiological condition of the organism, independent of its effect on metal availability. At the same time it explicitly considers the degree of interaction of these factors with the organism and how this affects the rate at which cumulative damage occurs. An example application of the model to toxicity data for rainbow trout exposed to silver is presented to illustrate how this framework may be used to predict survival time for alternative exposure durations. The sodium balance model (SBM) that is described herein, a specific application of a more generic ion balance model (IBM) framework, adds a new physiological dimension to the previously developed BLM. As such it also necessarily adds another layer of complexity to this already useful predictive framework. While the demonstrated capability of the SBM to predict effects in relation to exposure duration is a useful feature of this mechanistically-based framework, it is envisioned that, with suitable refinements, it may also have utility in other areas of toxicological and regulatory interest. Such areas include the analysis of time variable exposure conditions, residual after-effects of exposure to metals, acclimation, chronic toxicity and species and genus sensitivity. Each of these is of potential utility to longer-term ongoing efforts to develop and refine WQC for metals.     

Carving the cognitive niche: optimal learning strategies in homogeneous and heterogeneous environments

A model learning system is constructed, in which an organism samples behaviors from a behavioral repertoire in response to a stimulus and selects the behavior with the highest payoff. The stimulus and most rewarding behavior may be kept in the organism's long-term memory and reused if the stimulus is encountered again. The value of the memory depends on the reliability of the stimulus, that is, how the corresponding payoffs of behaviors change over time. We describe how the inclusion of memory can increase the optimal sampling size in environments with some stimulus reliability. In addition to using memory to guide behavior, our organism may use information in its memory to choose the stimulus to which it reacts. This choice is influenced by both the organism's memory state and how many stimuli the organism can observe (its sensory capability). The number of sampled behaviors, memory length, and sensory capability are the variables that define the learning strategy. When all stimuli have the same reliability, there appears to be only a single optimal learning strategy. However, when there is heterogeneity in stimulus reliability, multiple locally optimal strategies may exist.     

What renders <Emphasis Type="Italic">Bacilli</Emphasis> genetically competent? A gaze beyond the model organism

Natural genetic competence enables bacteria to take in and establish exogenously supplied DNA and thus constitutes a valuable tool for strain improvement. Extensively studied in the Gram-positive model organism Bacillus subtilis genetic competence has indeed proven successful for genetic manipulation aiming at enhancement of handling, yield, and biosafety. The majority of Bacilli, particularly those relevant for industrial application, do not or only poorly develop genetic competence, although rather homologous DNA-uptake machineries are routinely encoded. Establishing the competent state solely due to high cell densities (quorum sensing dependency) appears to be restricted to the model organism, in which the small signalling peptide ComS initiates the regulatory pathway that ultimately leads to the expression of all genes necessary for reaching the competent state. Agreeing with the lack of a functional ComS peptide, competence-mediated transformation of other Bacilli depends on nutrient exhaustion rather than cell density. Genetically, competent strains of the model organism B. subtilis, cultivated for a long time and selected for laboratory purposes, display probably not least to such selection a point mutation in the promoter of a regulatory gene that favors competence development whereas the wild-type progenitor only poorly displays genetic competence. Consistent with competence being a matter of deregulation, all strains of Bacillus licheniformis displaying efficient DNA uptake were found to carry mutations in regulator genes, which are responsible for their genetic competence. Thus, strain-specific genetic equipment and regulation as well as the proven role of domestication for the well-established laboratory strains ought to be considered when attempting to broaden the applicability of competence as a genetic tool for strains other than the model organism.     

Parallel Representation of Value-Based and Finite State-Based Strategies in the Ventral and Dorsal Striatum

Previous theoretical studies of animal and human behavioral learning have focused on the dichotomy of the value-based strategy using action value functions to predict rewards and the model-based strategy using internal models to predict environmental states. However, animals and humans often take simple procedural behaviors, such as the “win-stay, lose-switch” strategy without explicit prediction of rewards or states. Here we consider another strategy, the finite state-based strategy, in which a subject selects an action depending on its discrete internal state and updates the state depending on the action chosen and the reward outcome. By analyzing choice behavior of rats in a free-choice task, we found that the finite state-based strategy fitted their behavioral choices more accurately than value-based and model-based strategies did. When fitted models were run autonomously with the same task, only the finite state-based strategy could reproduce the key feature of choice sequences. Analyses of neural activity recorded from the dorsolateral striatum (DLS), the dorsomedial striatum (DMS), and the ventral striatum (VS) identified significant fractions of neurons in all three subareas for which activities were correlated with individual states of the finite state-based strategy. The signal of internal states at the time of choice was found in DMS, and for clusters of states was found in VS. In addition, action values and state values of the value-based strategy were encoded in DMS and VS, respectively. These results suggest that both the value-based strategy and the finite state-based strategy are implemented in the striatum.     

Stochastic model for analysis of longitudinal data on aging and mortality

Aging-related changes in a human organism follow dynamic regularities, which contribute to the observed age patterns of incidence and mortality curves. An organism's 'optimal' (normal) physiological state changes with age, affecting the values of risks of disease and death. The resistance to stresses, as well as adaptive capacity, declines with age. An exposure to improper environment results in persisting deviation of individuals' physiological (and biological) indices from their normal state (due to allostatic adaptation), which, in turn, increases chances of disease and death. Despite numerous studies investigating these effects, there is no conceptual framework, which would allow for putting all these findings together, and analyze longitudinal data taking all these dynamic connections into account. In this paper we suggest such a framework, using a new version of stochastic process model of aging and mortality. Using this model, we elaborated a statistical method for analyses of longitudinal data on aging, health and longevity and tested it using different simulated data sets. The results show that the model may characterize complicated interplay among different components of aging-related changes in humans and that the model parameters are identifiable from the data.