Why we should use simpler models if the data allow this: relevance for ANOVA designs in experimental biology

Background  

Analysis of variance (ANOVA) is a common statistical technique in physiological research, and often one or more of the independent/predictor variables such as dose, time, or age, can be treated as a continuous, rather than a categorical variable during analysis – even if subjects were randomly assigned to treatment groups. While this is not common, there are a number of advantages of such an approach, including greater statistical power due to increased precision, a simpler and more informative interpretation of the results, greater parsimony, and transformation of the predictor variable is possible.     

Comparative biology and pathology of oxidative stress in Alzheimer and other neurodegenerative diseases: beyond damage and response

In this review, we consider comparative aspects of the biology and pathology of oxygen radicals in neurodegenerative disease and how these findings have influenced our concept of oxidative stress. The common definition of oxidative stress is a breach of antioxidant defenses by oxygen radicals leading to damage to critical molecules and disrupted physiology. Inherent in this definition is that oxidative stress is an unstable situation, for if there is net damage, viability of the system decreases with time, leading to disequilibria and death. While this circumstance defines acute conditions, such as stroke and head trauma which result in dysfunction and death, it does not fit physiological situations or chronic diseases closely aligned to normal physiology. Therefore, we propose that oxidative modifications in Alzheimer disease may actually serve as a homeostatic response to stress resulting in a shift of neuronal priority from normal function to basic survival. This phenomenon is comparable to normal physiological conditions of metabolic decrease, such as those seen in hibernation and estivation. Thus, Alzheimer disease could be seen as part of normal aging that includes additional pathology due to inadequate homeostatic response.     

Dynamic structure theory: A structural approach to social and biological systems

The relationships that define the structure of a given ecosystem, social system, or even a physiological function can only exist if certain parameters are confined to a certain range of values. As the values change and exceed this given range the relationships are forced to change, and so produce a new pattern of relationships. The concept of a dynamic structure captures this potential for structural change in relation to a set of parameters. The precise definition of structure and allowable transformation constitutes the definition of a category. The total range of parameters associated with all the relevant structures provides a parameter space which is assumed to be a manifold. Maps with extra structure from the manifold to the category define dynamic structures. The domain of differential dynamic systems is the manifold, and a flow or movement across the manifold is associated with a series of structural transformations in the category. In some cases a structure outruns its parameter range, to be faced with an obstruction—an absence of possible transformations. Ways of studying such “obstructions” are considered along with the related problem of extending a dynamic structure beyond a previously given set of parameters. The cost or resistance of transformations is also studied. The concepts of dynamic structures are illustrated by the structural change of food webs and they are used in a necessarily qualitative fashion to study dominance structures of social orders and finally to speculate on the qualitative nature of evolutionary change of functional aspects of organisms.     

Roles for learning in mammalian chemosensory responses

This article is part of a Special Issue “Chemosignals and Reproduction”.A rich variety of chemosignals have been identified that influence mammalian behaviour, including peptides, proteins and volatiles. Many of these elicit innate effects acting either as pheromones within species or allelochemicals between species. However, even innate pheromonal responses in mammals are not as hard-wired as the original definition of the term would suggest. Many, if not most mammalian pheromonal responses are only elicited in certain behavioural or physiological contexts. Furthermore, certain pheromones are themselves rewarding and act as unconditioned stimuli to link non-pheromonal stimuli to the pheromonal response, via associative learning. The medial amygdala, has emerged as a potential site for this convergence by which learned chemosensory input is able to gain control over innately-driven output circuits. The medial amygdala is also an important site for associating social chemosensory information that enables recognition of conspecifics and heterospecifics by association of their complex chemosensory signatures both within and across olfactory chemosensory systems. Learning can also influence pheromonal responses more directly to adapt them to changing physiological and behavioural context. Neuromodulators such as noradrenaline and oxytocin can plasticise neural circuits to gate transmission of chemosensory information. More recent evidence points to a role for neurogenesis in this adaptation, both at the peripheral level of the sensory neurons and via the incorporation of new neurons into existing olfactory bulb circuits. The emerging picture is of integrated and flexible responses to chemosignals that adapt them to the environmental and physiological context in which they occur.     

Desensitization and coupled receptors: a model of drug dependence

It is assumed that certain drug receptors are so coupled with certain physiological receptors that stimulation of either receptor increases the sensitivity of the other. If the drug receptor suffers tolerance (i.e. slow desensitization) and if insensitivity of the drug receptor also makes the physiological receptor insensitive, then tolerance must be responsible for a physiological deficiency. This may be remedied by increased drug administration which will raise the sensitivity of the remaining physiological receptors so that a normal or near-normal physiological situation is achieved. Thus the organism is not only tolerant to the drug but also dependent on it. If such theoretical considerations apply to opiate receptors (as drug receptors) and to catecholamine receptors (as physiological receptors), then the theory predicts that acute morphine administration increases the sensitivity of dopamine receptors, that sympathetic stimulation decreases pain sensitivity, that opioid tolerance provokes increased catecholamine activity, that alpha-receptor stimulants attenuate and alpha-receptor antagonists exacerbate morphine abstinence, and that catecholaminergic inhibition results in increased morphine toxicity. All of these predictions have been verified experimentally.     

Stochastic Heterogeneous Interaction Promotes Cooperation in Spatial Prisoner's Dilemma Game

Previous studies mostly investigate player''s cooperative behavior as affected by game time-scale or individual diversity. In this paper, by involving both time-scale and diversity simultaneously, we explore the effect of stochastic heterogeneous interaction. In our model, the occurrence of game interaction between each pair of linked player obeys a random probability, which is further described by certain distributions. Simulations on a 4-neighbor square lattice show that the cooperation level is remarkably promoted when stochastic heterogeneous interaction is considered. The results are then explained by investigating the mean payoffs, the mean boundary payoffs and the transition probabilities between cooperators and defectors. We also show some typical snapshots and evolution time series of the system. Finally, the 8-neighbor square lattice and BA scale-free network results indicate that the stochastic heterogeneous interaction can be robust against different network topologies. Our work may sharpen the understanding of the joint effect of game time-scale and individual diversity on spatial games.     

A note on the interpretation of tree-based regression models

Tree-based models are a popular tool for predicting a response given a set of explanatory variables when the regression function is characterized by a certain degree of complexity. Sometimes, they are also used to identify important variables and for variable selection. We show that if the generating model contains chains of direct and indirect effects, then the typical variable importance measures suggest selecting as important mainly the background variables, which have a strong indirect effect, disregarding the variables that directly influence the response. This is attributable mainly to the variable choice in the first steps of the algorithm selecting the splitting variable and to the greedy nature of such search. This pitfall could be relevant when using tree-based algorithms for understanding the underlying generating process, for population segmentation and for causal inference.     

Criteria for excitation and inhibition in peristimulus spike train activity

1) Five possibilities of defining a coefficient of facilitation and inhibition are described. 2) It is shown that the application of these definition to the same spike train activity eventually leads to considerably different results, e.g., a response which is inhibitory according to one definition sometimes is facilitatory according to another definition. 3) To find the most reliable definition the theoretical differences between the five alternatives are examined, whereby a coefficient is considered reliable if it is reproducible and independent of external experimental parameters, such as the record length. 4) As an experimental example spike trains were recorded from mitral cells in the olfactory bulb of the goldfish. We divide every response into two sections: an initial reaction and a steady state reaction. In this way each response can be uniquely classified. 5) The most reliable definition of a coefficient of facilitation turns out to be based on the steady state levels of an averaged peristimulus time histogramme. Under certain conditions this corresponds to considering the means of the sample mean rates of a stochastic point process before and after the stimulus application, whereby the initial reactions are neglected. These should be classified by other methods and notions.     

Semiparametric estimation of random effects using the Cox model based on the EM algorithm.

Consider a survival experiment where individuals within a certain subset of the population share a common, unobservable, random frailty. Such a frailty could be an unobservable genetic or early environmental effect if individuals were in sibling groups or an environmental effect if individuals were grouped by households. Suppose that if the frailty, omega, is known, the Cox proportional hazards model for the observable covariates is valid with the consequence of the random effect being a multiplicative factor on the hazard rate. Assuming tht the random frailties follow a gamma distribution, estimates of the fixed and random effects are obtained by using an EM algorithm based on a profile likelihood construction. The method developed is applied to the Framingham Heart Study to examine the risks of smoking and cholesterol levels, adjusting for potential random effects.     

Estimation of the Life Span of Red Blood Cells in the Growing Animal in Different Nutritional States

In this study the model of Shemin and Rittenberg for estimating the life span of red blood cells was extended so that non-steady-state conditions, exemplified by growth or changing physiological states, might be considered. The parameters were estimated by use of the modified Gauss-Newton method. The biological data that were used came from growing sheep in different physiological states with regard to copper. The model was extended to include changes in total blood hemin and changes in blood hemin synthesis that may occur with time. In the present study a linear function was taken as a first approximation. The model appeared to be a sufficiently good approximation in the study reported herein. It was found, however, that the parameters associated with changes in hemin should be estimated from ancillary measurements such as blood volume, Hb, body weight, etc., in order to obtain a good fit or definition of the model.     

Variable noding in Cyprideis torosa (Ostracoda,Crustacea): an overview,experimental results and a model from Catastrophe Theory

Various anomalohaline ostracod species will, under certain conditions, develop hollow, outward flexions of the lateral surface of their carapace that are called nodes. While the potential positions on the shell surface of such nodes are normally fixed, their number and relative strength are variable. This phenomenon, which is called variable noding, is best known in Cyprideis torosa (Jones, 1850) but it actually features in several more species of Cyprideis and other cytherideinid genera, both Recent and fossil. Alternately explaining it as ecophenotypic or genotypic, nearly all primary sources in the literature associate variable noding with low environmental salinity. Culturing results confirm that the phenomenon reflects a direct physiological response rather than a genotypic adaptation. From the cultures, it also appears, however, that there is yet another factor active, in addition to and interfering with environmental salinity. This factor is provisionally called `factor X'. The experiments suggest that factor X may represent either the pH or the CO₂ content of the ambient water, and hence be directly related to dissolved CaCO₃. With two interfering factors, variable noding can possibly be described by the cusp model of Catastrophe Theory with salinity and factor X as the controls and noding capability as the resultant reaction surface. Lacking sufficient calibration, the model must remain qualitative for the time being. Further experimentation and careful observation in the field should allow its quantification, thus clearing the path for palaeoecological application.     

The impact of diffusion and stirring on the dynamics of interacting populations

We investigate the combined effects of diffusion and stirring on the dynamics of interacting populations which have spatial structure. Specifically we consider the marine phytoplankton and zooplankton populations, and model them as an excitable medium. The results are applicable to other biological and chemical systems. Under certain conditions the combination of diffusion and stirring is found to enhance the excitability, and hence population growth of the system. Diffusion is found to play an important role: too much and initial perturbations are smoothed away, too little and insufficient mixing takes place before the reaction is over. A key time-scale is the mix-down time, the time it takes for the spatial scale of a population to be reduced to that of a diffusively controlled filament. If the mix-down time is short compared to the reaction time-scale, then excitation of the system is suppressed. For intermediate values of the mix-down time the peak population can attain values many times that of a population without spatial structure. We highlight the importance of the spatial scale of the initial disturbance to the system.     

Holding of juvenile salmonids for surgical implantation of electronic tags: a review and recommendations

Many telemetry-based studies require that fish be sampled from the wild and then held both prior to and after the implantation of an electronic tag. However, the effects of such holding (or the lack thereof) have yet to be studied intensively. Pre-surgical holding often occurs to facilitate logistical needs of research projects and as an attempt to minimize negative physiological effects due to capture and handling stress. Further, post-surgical holding time and conditions greatly influence the physiological state of fish prior to being returned to the wild. This paper reviews pertinent studies pertaining to the effects of surgical holding on the behavior, physiology, and survival of fishes, with particular emphasis on juvenile salmonids. The effects of individual aspects of surgical holding such as handling, water quality, light conditions, holding density, metabolic scope, and duration of holding are reviewed. Recommendations regarding certain aspects of surgical holding are offered with a goal of reducing bias related to the surgical process.     

Non‐parametric habitat models with automatic interactions

Questions: Can a statistical model be designed to represent more directly the nature of organismal response to multiple interacting factors? Can multiplicative kernel smoothers be used for this purpose? What advantages does this approach have over more traditional habitat modelling methods? Methods: Non‐parametric multiplicative regression (NPMR) was developed from the premises that: the response variable has a minimum of zero and a physiologically‐determined maximum, species respond simultaneously to multiple ecological factors, the response to any one factor is conditioned by the values of other factors, and that if any of the factors is intolerable then the response is zero. Key features of NPMR are interactive effects of predictors, no need to specify an overall model form in advance, and built‐in controls on overfitting. The effectiveness of the method is demonstrated with simulated and real data sets. Results: Empirical and theoretical relationships of species response to multiple interacting predictors can be represented effectively by multiplicative kernel smoothers. NPMR allows us to abandon simplistic assumptions about overall model form, while embracing the ecological truism that habitat factors interact.     

生精细胞凋亡相关基因

细胞凋亡(apoptosis)是一种基因控制的细胞生理性自杀行为,用以维持细胞数量的相对恒定,可由某种刺激或抑制剂的移除而激活。在哺乳动物精子发生过程中,各级生精细胞都会发生相应的凋亡,通过严格调控以确保成熟精子生成的数量和质量。生精细胞的凋亡是一个许多基因参与的复杂的不可逆过程,其中Bcl-2/Bax基因族、p53基因、Fas-Fasl基因、C-myc基因、CREM基因、HSP基因族、c-Kit/SCF基因、Insl3基因、iNOS基因、BMP8B基因、TR基因和存活蛋白(survivin)基因等发挥了重要作用。研究哺乳动物睾丸生精细胞凋亡相关基因,有利于了解生精细胞凋亡机制,为进一步阐明精子发生的调控机制,预防和治疗精子发生相关疾病提供重要的理论依据。     

What is all the noise about in interval timing?

Cognitive processes such as decision-making, rate calculation and planning require an accurate estimation of durations in the supra-second range—interval timing. In addition to being accurate, interval timing is scale invariant: the time-estimation errors are proportional to the estimated duration. The origin and mechanisms of this fundamental property are unknown. We discuss the computational properties of a circuit consisting of a large number of (input) neural oscillators projecting on a small number of (output) coincidence detector neurons, which allows time to be coded by the pattern of coincidental activation of its inputs. We showed analytically and checked numerically that time-scale invariance emerges from the neural noise. In particular, we found that errors or noise during storing or retrieving information regarding the memorized criterion time produce symmetric, Gaussian-like output whose width increases linearly with the criterion time. In contrast, frequency variability produces an asymmetric, long-tailed Gaussian-like output, that also obeys scale invariant property. In this architecture, time-scale invariance depends neither on the details of the input population, nor on the distribution probability of noise.     

Disequilibrium in Two-Locus Mutation-Selection Balance Models

Equilibrium behavior of two-locus mutation-selection balance models is analyzed using perturbation techniques. The classical result of Haldane for one locus is shown to carry over to two loci, if fitnesses are replaced by marginal fitnesses. If the fitness of the double heterozygote is smaller than would be produced by a multiplicative model, as in additive or quantitative fitness models, the disequilibrium is negative--an excess of gametes with one rare allele. In this case the disequilibrium can be as large as one-half its maximum value possible, if the recombination rate is small, not greater than the strength of selection. If the fitness of the double heterozygote is larger than would be produced by a multiplicative model, the disequilibrium is positive, and is very small relative to its maximum value possible, even if the recombination rate is zero.     

EVOLUTIONARILY STABLE SIZE OF A MEGAGAMETOPHYTE: EVOLUTION OF TINY MEGAGAMETOPHYTES OF ANGIOSPERMS FROM LARGE ONES OF GYMNOSPERMS

To examine the factors favoring large megagametophytes of gymnosperms and tiny ones of angiosperms, a game model for seed production was developed in which megagametophytes growing in the same female parent compete for resources provided by the parent. In the model, megagametophytes may continue to grow until seed completion or may cease to grow at a certain time and regrow at pollination or fertilization. Autonomous abortion of unpollinated or unfertilized megagametophytes may occur either at pollination or fertilization. Those megagametophytes absorb a certain amount of resources before abortion, due to constraints in the signal process, in addition to the resources absorbed before pollination or fertilization. It was found that both growth habits can be the ESS: megagametophytes continue to grow without cessation and monopolize resources, such as gymnosperms, or cease to grow until fertilization to reduce the loss of resources due to autonomous abortion, such as angiosperms. The former and the latter are the ESS if the time interval between pollination and fertilization is long and short, respectively. Thus, the fertilization interval may be a critical factor selecting for large megagametophytes of gymnosperms or tiny ones of angiosperms.