Penna Model For Biological Aging Research Articles

Model on Impingement and consequences of Alzheimer’s disease in community‐ introductory study.

AbstractBackgroundAlzheimer disease demands salutation and envisioning the cause for the disease. Despite the evolving scientific discoveries, the inhabitation among the global population reminds hiking alarmingly. The track of ways the spread of disease should leave a hint for the further research on the origin of the disease.MethodThis is a speculation much closure to current environment, to analyze effect and the pace of spread over a community. Penna model of biological aging [1] and model of colonization (lattice model) [2] are primitive base. For the model both inherited and non‐ inherited Alzheimer disease is taken into account and is obtruded into the lattice simulated on external factors such as age, genome, genetic mutation, mating partner, offspring and visualizing the change in population, symptoms and progress of the disease.ResultOutcome helps in providing an introductory knowledge on the impact Alzheimer creates in the society. It shows the growth on the level of symptoms in the population, the influence of the inheritance on the population and their progress during the course of time. The symptom to analyze the level of disease at respective age of the individual is monitored. The executions for variations in the input arguments are studied to determine the effect of disease from different perspectives.ConclusionThe Preliminary results show reasonable changes on the level of symptoms for the inherited Alzheimer’s disease. The results shell out some introductory ideas about growth of the level of symptoms of AD in the population during the course of the disease increasing number of offspring and number of mating will give a greater view of the consequences in the model and is predictable for the current scenario.1. Stauffer, D. (2007). The Penna model of biological aging. Bioinformatics and Biology Insights, 1, 117793220700100005.2. Mroz, I., &Pękalski, A. (1999). Model of populations colonizing a new habitat. The European Physical Journal B‐Condensed Matter and Complex Systems, 10(1), 181‐186.

Simulations of populations of Sapajus robustus in a fragmented landscape

The study of populations subject to the phenomenon of loss and fragmentation of habitat, transforming continuous areas into small ones, usually surrounded by anthropogenic matrices, has been the focus of many researches within the scope of conservation. The objective of this study was to develop a computer model by introducing modifications to the renowned Penna model for biological aging, in order to evaluate the behavior of populations subjected to the effects of fragmented environments. As an object of study, it was used biological data of the robust tufted capuchin (Sapajus robustus), an endangered primate species whose geographical distribution within the Atlantic Rain Forest is part of the backdrop of intense habitat fragmentation. The simulations showed the expected behavior based on the three main aspects that affects populations under intense habitat fragmentation: the population density, area and conformation of the fragments and deleterious effects due the low genetic variability in small and isolated populations. The model showed itself suitable to describe changes in viability and population dynamics of the species crested capuchin considering critical levels of survival in a fragmented environment and also, actions in order to preserve the species should be focused not only on increasing available area but also in dispersion dynamics.

Epigenetic contribution to age distribution of mortality within the Penna model.

Some modifications of the simple asexual Penna model, enriched by epigenetic contributions, are presented. The standard bit-string Penna model of biological aging and population evolution is based on an inherited DNA structure which defines the future life of a newly born individuals, when genes are activated by the biological clock, and the predefined genetic death is fully controlled by the number of defected genes. Epigenomes allow to introduce additional mechanism of gene activation or silencing without affecting the DNA genome itself. It may be either inherited or may reflect external, environmental factors. In the presented model, information read from the introduced epigenome may alter gene expression that may be stopped or re-activated. We concentrate on the influence of epigenetics on the age a distribution of genetic mortality m(a). Changes in m(a) are strong for the case of inherited epigenetic contribution with nearly perfect inheritance and 'positive' epigenome that partly ignores the 'bad' mutations. We conclude that the epigenetic contribution may influence population structure m(a) and could be, at least partly, responsible for deviation of m(a) distribution from the Gompertz law. In short, we claim that proposed epigenetic contribution may be seen as a candidate for possible explanation of observed deviation from the Gompertz law, also among senior members of society. A very simple model was used in this paper and many crucial mechanisms of biological aging were omitted. Therefore, further work based on a more realistic models is necessary.

On Evolution of Migrating Population with Two Competing Species

A computer experiment study of population evolution and its dynamics is pre- sented for two competing species (A and B) which share two habitats (1 and 2) of a limited environmental capacity. The Penna model of biological aging, based on the concept of defective mutation accumulation, was adopted for mi- grating population. In this paper, we assume and concentrate on the case when only one species (A) is mobile. For isolated habitats and for any initial popu- lation, we get at equilibrium spatial population distribution (A, B) in which A occupies location '1' only, while B-species is the ultimate winner in '2'. This is achieved by suitable choice of model parameters so habitat '1' is more at- tractive for species 'A' while location '2' is more advantageous to 'B'. However, population distribution begins to dier when migration between habitats is al-

Evolution of species from Darwin theory: A simple model

Evolution of species is a complex phenomenon. Some theoretical models take into account evolution of species, like the Bak–Sneppen model that obtain punctuated equilibrium from self-organized criticality and the Penna model for biological aging that consists in a bit-string model subjected to aging, reproduction and death. In this work we propose a simple model to study different scenarios used to simulate the evolution of species. This model is based on Darwin’s ideas of evolution. The present findings show that punctuated equilibria and stasis seem to be obtained directly from the mutation, selection of parents and the genetic crossover, and are very close to the fossil data analysis.

Numerical solution of the Penna model of biological aging with age-modified mutation rate

In this paper we present results of numerical calculation of the Penna bit-string model of biological aging, modified for the case of a -dependent mutation rate m(a), where a is the parent's age. The mutation rate m(a) is the probability per bit of an extra bad mutation introduced in offspring inherited genome. We assume that m(a) increases with age a. As compared with the reference case of the standard Penna model based on a constant mutation rate m , the dynamics of the population growth shows distinct changes in age distribution of the population. Here we concentrate on mortality q(a), a fraction of items eliminated from the population when we go from age (a) to (a+1) in simulated transition from time (t) to next time (t+1). The experimentally observed q(a) dependence essentially follows the Gompertz exponential law for a above the minimum reproduction age. Deviation from the Gompertz law is however observed for the very old items, close to the maximal age. This effect may also result from an increase in mutation rate m with age a discussed in this paper. The numerical calculations are based on analytical solution of the Penna model, presented in a series of papers by Coe et al. [J. B. Coe, Y. Mao, and M. E. Cates, Phys. Rev. Lett. 89, 288103 (2002)]. Results of the numerical calculations are supported by the data obtained from computer simulation based on the solution by Coe et al.

Stability of the analytical solution of Penna model of biological aging

There are some analytical solutions of the Penna model of biological aging; here, we discuss the approach by Coe et al. (Phys. Rev. Lett. 89, 288103, 2002), based on the concept of self-consistent solution of a master equation representing the Penna model. The equation describes transition of the population distribution at time t to next time step (t + 1). For the steady state, the population n(a, l, t) at age a and for given genome length l becomes time-independent. In this paper we discuss the stability of the analytical solution at various ranges of the model parameters--the birth rate b or mutation rate m. The map for the transition from n(a, l, t) to the next time step population distribution n(a + 1, l, t + 1) is constructed. Then the fix point (the steady state solution) brings recovery of Coe et al. results. From the analysis of the stability matrix, the Lyapunov coefficients, indicative of the stability of the solutions, are extracted. The results lead to phase diagram of the stable solutions in the space of model parameters (b, m, h), where h is the hunt rate. With increasing birth rate b, we observe critical b (0) below which population is extinct, followed by non-zero stable single solution. Further increase in b leads to typical series of bifurcations with the cycle doubling until the chaos is reached at some b (c). Limiting cases such as those leading to the logistic model are also discussed.

The Penna Model of Biological Aging

This review deals with computer simulation of biological aging, particularly with the Penna model of 1995. They are based on the mutation accumulation theory of half a century ago. The results agree well with demographical reality, and also with the seemingly contradictory influence of predators on the aging of prey.

Simulations of a mortality plateau in the sexual Penna model for biological aging

The Penna model is a strategy to simulate the genetic dynamics of age-structured populations, in which the individual genomes are represented by bit strings. It provides a simple metaphor for the evolutionary process in terms of the mutation accumulation theory. In its original version, an individual dies due to inherited diseases when its current number of accumulated mutations, n, reaches a threshold value T. Since the mean number of diseases increases with age, the probability to die is zero for very young ages (n < T) and equals 1 for the old ones (n > or = T). Here, instead of using a step function to determine the genetic death age, we test several other functions that may or may not slightly increase the death probability at young ages (n < T), but that decrease this probability at old ones. Our purpose is to study the oldest old effect, that is, a plateau in the mortality curves at advanced ages. By imposing certain conditions, it has been possible to obtain a clear plateau using the Penna model. However, a more realistic one appears when a modified version, that keeps the population size fixed without fluctuations, is used. We also find a relation between the birth rate, the age structure of the population, and the death probability.

SIMULATION AND EXPERIMENT OF EXTINCTION OR ADAPTATION OF BIOLOGICAL SPECIES AFTER TEMPERATURE CHANGES

Can unicellular organisms survive a drastic temperature change, and adapt to it after many generations? In simulations of the Penna model of biological aging, both extinction and adaptation were found for asexual and sexual reproduction as well as for parasex. These model investigations are the basis for the design of evolution experiments with heterotrophic flagellates.

A Modified Penna Model for Biological Aging

The Penna model for biological aging was modified. The reproducibility of each individual was determined according to the number of mutations relevant at that time. The results of Monte-Carlo calculations using the modified model show that the ranges of the reproducible age are broadened as time goes by, thus showing self-organization in biological aging to the direction of maximum self-conservation. In addition, the population, survival rate, and average life span were calculated and analyzed by changing the number of new mutations at birth. It is observed that the more the number of new mutations at birth is considered, the shorter the average life span that is obtained.

SELF-ORGANIZATION OF AGING IN A MODIFIED PENNA MODEL

The Penna model for biological aging is modified so that the fertility of each individual is determined by means of the number of activated mutations at that time. A new concept of "good" mutation, which makes an individual to mature enough to reproduce, is introduced. It is assumed that each individual can reproduce only during adulthood, which is determined by the number of activated mutations. The results of Monte Carlo calculations using the modified model show that the ranges of the reproductive age are broadened as time goes by, thus showing self-organization in the biological aging to the direction of the maximum self-conservation. In addition, the population, the survival rate, and the average life span were calculated and analyzed by changing the number of new mutations at birth. It is observed that the higher is the considered number of new mutations at birth, the shorter is the obtained average life span. The mortality functions are also calculated and they showed the exponential increase in adulthood, satisfying the Gompertz law.

Sympatric speciation in an age-structured population living on a lattice

A square lattice is introduced into the Penna model for biological aging in order to study the evolution of diploid sexual populations under certain conditions when one single locus in the individual's genome is considered as identifier of species. The simulation results show, after several generations, the flourishing and coexistence of two separate species in the same environment, i.e., one original species splits up into two on the same territory (sympatric speciation). As well, the mortalities obtained are in a good agreement with the Gompertz law of exponential increase of mortality with age.

The penna model for biological aging and speciation

The penna model for biological aging and speciation

PENNA BIT-STRING MODEL WITH CONSTANT POPULATION

We removed from the Penna model for biological aging any random killing Verhulst factor. Deaths are due only to genetic diseases and the population size is fixed, instead of fluctuating around some constant value. We show that these modifications give qualitatively the same results obtained in an earlier paper, where the random killings (used to avoid an exponential increase of the population) were applied only to newborns.

Positive mutations and mutation-dependent Verhulst factor in Penna ageing model

We modify twice the Penna model for biological ageing. First, we introduce back (good) mutations and a memory for them into the model. It allows us to observe an improvement of the species fitness over long-time scales as well as punctuated equilibrium. Second, we adopt a food/space competition factor that depends on the number of accumulated mutations in the individuals genomes, and get rid of the fixed limiting number of allowed mutations. Besides reproducing the main results of the standard model, we also observe a mortality maximum for the oldest old.

Evolutionary advantage of diploidal over polyploidal sexual reproduction.

We modify the Penna model for biological aging, which is based on the mutation-accumulation theory, in order to verify if there would be any evolutionary advantage of triploid over diploid organisms. We show that this is not the case, and that diploidal sex is always better than that involving three individuals.

APPLICATIONS AND SEXUAL VERSION OF A SIMPLE MODEL FOR BIOLOGICAL AGING

We use a simple model for biological aging to study the mortality of the population, obtaining a good agreement with the Gompertz law. We also simulate the same model on a square lattice, considering different strategies of parental care. The results are in agreement with those obtained earlier with the more complicated Penna model for biological aging. Finally, we present the sexual version of this simple model.

The sex-specific life expectancy and the influence of testosterone in a mathematical aging simulation model and its consequences for prevention

There are many explanations for the sex-specific difference in life expectancy. An important reason for this difference can be found in the genome difference of one sex chromosome. It is obvious that testosterone, as an effective hormonal product of this genome difference, influences not only morphology, physiology and risk profiles of diseases but also social behavior and lifestyle. Statistical simulations are, for physicians, an unusual way to demonstrate differences in human mortality, but they may help to show other, and more abstract, aspects of nature. The Penna model of biological aging is a well-established model for simulating the influence of genetic factors on sex-specific mortality. In this study, the Penna model is explained and modified to take into account the potentially detrimental effects of testosterone on male mortality. This is achieved by a modification of the Verhulst factor, starting with male puberty. We demonstrated that about one-third of the sex-specific difference in life expectancy may be caused by the influence of testosterone in this mathematical aging model. These results do not show that male vices (smoking, drinking, risk-taking behavior, etc.) can be attributed only to testosterone even though it may appear so from the statistics. There are some correlations but not causal relations. It seems, even from the view of a mathematical–statistical simulation, that males are discriminated against regarding mortality and life expectancy. This underlines the need for sex-specific research, social policy and preventive programs (e.g. sports, nutrition) for minimizing the negative impact of male-specific genetic and hormonal factors.

An unusual antagonistic pleiotropy in the Penna model for biological ageing

We combine the Penna Model for biological ageing, which is based on the mutation-accumulation theory, with a sort of antagonistic pleiotropy. We show that depending on how the pleiotropy is introduced, it is possible to reproduce both the humans mortality, which increases exponentially with age, and fruitfly mortality, which decelerates at old ages, allowing the appearance of arbitrarily old Methuselah's.