Acta Biotheoretica

A Word of Welcome to Our New Editorial Board Members, and Presentation of the New Editorial Board

An Organisational Approach to Biological Communication Abstract This paper aims to provide a philosophical and theoretical account of biological communication grounded in the notion of organisation. The organisational approach characterises living systems as organised in such a way that they are capable to self-produce and self-maintain while in constant interaction with the environment. To apply this theoretical framework to the study of biological communication, we focus on a specific approach, based on the notion of influence, according to which communication takes place when a signal emitted by a sender triggers a change in the behaviour of the receiver that is functional for the sender itself. We critically analyse the current formulations of this account, that interpret what is functional for the sender in terms of evolutionary adaptations. Specifically, the adoption of this etiological functional framework may lead to the exclusion of several phenomena usually studied as instances of communication, and possibly even of entire fields of investigation such as synthetic biology. As an alternative, we reframe the influence approach in organisational terms, characterising functions in terms of contributions to the current organisation of a biological system. We develop a theoretical account of biological communication in which communicative functions are distinguished from other types of biological functions described by the organisational account (e.g. metabolic, ecological, etc.). The resulting organisational-influence approach allows to carry out causal analyses of current instances of phenomena of communication, without the need to provide etiological explanations. In such a way it makes it possible to understand in terms of communication those phenomena which realise interactive patterns typical of signalling interactions—and are usually studied as such in scientific practice—despite not being the result of evolutionary adaptations. Moreover, this approach provides operational tools to design and study communicative interactions in experimental fields such as synthetic biology.

Mathematical Modeling of Substrates Fluxes and Tumor Growth in the Brain Abstract The aim of this article is to show how a tumor can modify energy substrates fluxes in the brain to support its own growth. To address this question we use a modeling approach to explain brain nutrient kinetics. In particular we set up a system of 17 equations for oxygen, lactate, glucose concentrations and cells number in the brain. We prove the existence and uniqueness of nonnegative solutions and give bounds on the solutions. We also provide numerical simulations.

Multidrug Therapy for HIV Infection: Dynamics of Immune System Abstract A mathematical model of the dynamics of the immune system is considered to illustrate the effect of its response to HIV infection, i.e. on viral growth and on T-cell dynamics. The specific immune response is measured by the levels of cytotoxic lymphocytes in a human body. The existence and stability analyses are performed for infected steady state and uninfected steady state. In order to keep infection under control, roles of drug therapies are analyzed in the presence of efficient immune response. Numerical simulations are computed and exhibited to illustrate the support of the immune system to drug therapies, so as to ensure the decay of infection and to maintain the level of healthy cells.

The Coherence of Evolutionary Theory with Its Neighboring Theories Abstract Evolutionary theory coheres with its neighboring theories, such as the theory of plate tectonics, molecular biology, electromagnetic theory, and the germ theory of disease. These neighboring theories were previously unconceived, but they were later conceived, and then they cohered with evolutionary theory. Since evolutionary theory has been strengthened by its several neighboring theories that were previously unconceived, it will be strengthened by infinitely many hitherto unconceived neighboring theories. This argument for evolutionary theory echoes the problem of unconceived alternatives. Ironically, however, the former recommends that we take the realist attitude toward evolutionary theory, while the latter recommends that we take the antirealist attitude toward it.

Robust Model Selection and Estimation for Censored Survival Data with High Dimensional Genomic Covariates Abstract When relating genomic data to survival outcomes, there are three main challenges that are the censored survival outcomes, the high-dimensionality of the genomic data, and the non-normality of data. We propose a method to tackle these challenges simultaneously and obtain a robust estimation of detecting significant genes related to survival outcomes based on Accelerated Failure Time (AFT) model. Specifically, we include a general loss function to the AFT model, adopt model regularization and shrinkage technique, cope with parameters tuning and model selection, and develop an algorithm based on unified Expectation–Maximization approach for easy implementation. Simulation results demonstrate the advantages of the proposed method compared with existing methods when the data has heavy-tailed errors and correlated covariates. Two real case studies on patients are provided to illustrate the application of the proposed method.

Clearing New Ground

Walking the Line: A Tempered View of Contingency and Convergence in Life's History

Causally Modeling Adaptation to the Environment Abstract Brandon claims that to explain adaptation one must specify fitnesses in each selective environment and specify the distribution of individuals across selective environments. Glymour claims, using an example of the adaptive evolution of costly plasticity in a symmetric environment, that there are some predictive or explanatory tasks for which Brandon's claim is limited. In this paper, I provide necessary conditions for carrying out Brandon's task, produce a new version of the argument for his claim, and show that Glymour's reasons for making his claim are problematic. I provide a few interpretations of Glymour's argument but ultimately raise worries for what I take to be the key premises.

Control by Viability in a Chemotherapy Cancer Model Abstract The aim of this study is to provide a feedback control, called the Chemotherapy Protocol Law, with the purpose to keep the density of tumor cells that are treated by chemotherapy below a "tolerance level" \(L_c\) , while retaining the density of normal cells above a "healthy level" \(N_c\) . The mathematical model is a controlled dynamical system involving three nonlinear differential equations, based on a Gompertzian law of cell growth. By evoking viability and set-valued theories, we derive sufficient conditions for the existence of a Chemotherapy Protocol Law. Thereafter, on a suitable viability domain, we build a multifunction whose selections are the required Chemotherapy Protocol Laws. Finally, we propose a design of selection that generates a Chemotherapy Protocol Law.

Alexandros Sfakianakis
Anapafseos 5 . Agios Nikolaos
Crete.Greece.72100
2841026182

6948891480

alsfakia@gmail.com