JournalTOCs

Acta Biotheoretica
Journal Prestige (SJR): 0.284

Citation Impact (citeScore): 1
Number of Followers: 3

Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1572-8358 - ISSN (Online) 0001-5342
Published by Springer-Verlag

[2467 journals]

Fast Track Treatment of Hypothyroidism with Levothyroxine: Reaching
Homeostasis within Four Weeks
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  Abstract: Abstract With the current clinical method for the treatment of hypothyroidism the target for the optimum individual values for free thyroxine concentrations [FT4] and thyrotropine concentrations [TSH] of the specific patient are unknown. This situation leads to unnecessary long experimental medication administration that can take a period of sometimes one year. In this article a method will be described where hypothyroid patients are characterized with weekly measured FT4 and TSH concentrations during the first three weeks of synthetic thyroxine or levothyroxine (L-T4) treatment to predict their optimum [FT4] and belonging [TSH] endpoint for a euthyroid homeostatic state. The treatment with levothyroxine will start for all patients with a reference dose of 100 µg, which can be adjusted by the treating physician to a more safe and appropriate dose for the individual which is monitored with weekly thyroid function tests to observe the progress. After three weeks all characteristics of the patient can be inferred from the measured data. The final titration target together with the individual thyroxine half life can be calculated. With the known characteristics and the L-T4 titration target the clinician or treating physician has an instrument to reduce the experimental treatment burden for the patient from one year to a maximum of four weeks.
  PubDate: 2023-03-07
Mathematical Model of COVID-19 Pandemic with Double Dose Vaccination
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  Abstract: Abstract This paper is concerned with the formulation and analysis of an epidemic model of COVID-19 governed by an eight-dimensional system of ordinary differential equations, by taking into account the first dose and the second dose of vaccinated individuals in the population. The developed model is analyzed and the threshold quantity known as the control reproduction number \(\mathcal {R}_{0}\) is obtained. We investigate the equilibrium stability of the system, and the COVID-free equilibrium is said to be locally asymptotically stable when the control reproduction number is less than unity, and unstable otherwise. Using the least-squares method, the model is calibrated based on the cumulative number of COVID-19 reported cases and available information about the mass vaccine administration in Malaysia between the 24th of February 2021 and February 2022. Following the model fitting and estimation of the parameter values, a global sensitivity analysis was performed by using the Partial Rank Correlation Coefficient (PRCC) to determine the most influential parameters on the threshold quantities. The result shows that the effective transmission rate \((\alpha )\) , the rate of first vaccine dose \((\phi )\) , the second dose vaccination rate \((\sigma )\) and the recovery rate due to the second dose of vaccination \((\eta )\) are the most influential of all the model parameters. We further investigate the impact of these parameters by performing a numerical simulation on the developed COVID-19 model. The result of the study shows that adhering to the preventive measures has a huge impact on reducing the spread of the disease in the population. Particularly, an increase in both the first and second dose vaccination rates reduces the number of infected individuals, thus reducing the disease burden in the population.
  PubDate: 2023-03-06
Heuristics Facilitates the Evolution of Transitive Inference and Social
Hierarchy in a Large Group
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  Abstract: Abstract Transitive inference (TI) refers to social cognition that facilitates the discernment of unknown relationships between individuals using known relationships. It is extensively reported that TI evolves in animals living in a large group because TI could assess relative rank without deducing all dyadic relationships, which averts costly fights. The relationships in a large group become so complex that social cognition may not be developed adequately to handle such complexity. If members apply TI to all possible members in the group, TI requires extremely highly developed cognitive abilities especially in a large group. Instead of developing cognitive abilities significantly, animals may apply simplified TI we call reference TI in this study as heuristic approaches. The reference TI allows members to recognize and remember social interactions only among a set of reference members rather than all potential members. Our study assumes that information processes in the reference TI comprises (1) the number of reference members based on which individuals infer transitively, (2) the number of reference members shared by the same strategists, and (3) memory capacity. We examined how information processes evolve in a large group using evolutionary simulations in the hawk–dove game. Information processes with almost any numbers of reference members could evolve in a large group as long as the numbers of shared reference member are high because information from the others’ experiences is shared. TI dominates immediate inference, which assesses relative rank on direct interactions, because TI could establish social hierarchy more rapidly applying information from others’ experiences.
  PubDate: 2023-03-03
A Very Nice Meal with an Unsatisfying Appetizer
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  Abstract: Abstract As an Italian from the South, I have been socialized to care a lot about cooking. Quality of the food is a fundamental starting point for a successful result; in addition, you need expertise in food preparation and the capacity to balance dishes together in a single meal, from appetizer to dessert. I find Isabella Sarto-Jackson’s book The Making and Breaking of Mind a very nice meal with good-quality food prepared with expert hands, but the dish balance is a bit unsatisfying. I find dishes not always coherently combined with the general style of the meal, starting with the appetizer. A good appetizer would tell you what you should expect from the overall meal and would make you crave for tasting the rest. Instead, the book’s introduction and the first chapter seem to promise something different and does not give you a satisfactory idea of what you will read later. This is a pity, because overall the meal is quite nice, and most of the dishes delicious.
  PubDate: 2023-03-03
The Multi-Causal Basis of Developmental Potential Construction
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  Abstract: Abstract In this article we analyse the issue of what accounts for developmental potential, i.e., the possible phenotypes a developing organism can manifest during ontogeny. We shall argue in favour of two theses. First, although the developing organism is the unit of development, the complete causal basis for its potential to develop does neither lie entirely in itself as a whole nor in any specific part of itself (such as its genome). Thus, the extra-organismal environment must be counted as one of the three necessary, partial and complementary causal bases for development potential. Secondly, we shall defend a constructivist view of the developmental process. If the genome, the developing organism and the extra-organismal environment are to be counted as proper elements of the causal basis for an organism’s developmental potential, the latter is not a given. Rather, it is the result of an interaction-based construction, a process sometimes generating genuine developmental novelty. We will thus argue for an interactionist multi-causal basis view of developmental potential construction. We contend that our view provides a biologically tenable and metaphysically coherent account of developmental dynamics.
  PubDate: 2023-01-30
The Connection of the Generalized Robinson–Foulds Metric with
Partial Wiener Indices
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  Abstract: Abstract In this work we propose the partial Wiener index as one possible measure of branching in phylogenetic evolutionary trees. We establish the connection between the generalized Robinson–Foulds (RF) metric for measuring the similarity of phylogenetic trees and partial Wiener indices by expressing the number of conflicting pairs of edges in the generalized RF metric in terms of partial Wiener indices. To do so we compute the minimum and maximum value of the partial Wiener index \(W\left(T,r, n\right)\) , where \(T\) is a binary rooted tree with root \(r\) and \(n\) leaves. Moreover, under the Yule probabilistic model, we show how to compute the expected value of \(W\left(T,r, n\right)\) . As a direct consequence, we give exact formulas for the upper bound and the expected number of conflicting pairs. By doing so we provide a better theoretical understanding of the computational complexity of the generalized RF metric.
  PubDate: 2023-01-25
Model of Morphogenesis with Repelling Signaling
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  Abstract: Abstract The paper is devoted to a conceptual model of cell patterning, based on a generalized notion of the epigenetic code of a cell determining its state. We introduce the concept of signaling depending both upon the spatial distance between cells and the distance between their cell states (s-distance); signaling can repel cells in the space of cell states (s-space) or attract them. The influence of different types of repelling signaling on the evolution of cells is considered. Stabilizing signaling, namely a signaling monotonically decreasing with s-distance, causes the restoring of cell states after perturbations; destabilizing signaling, i.e., the one in which the signaling monotonically increases with s-distance, causes the appearance of pairs of cells with alternating cell states (one close to the state conventionally called “head”, and another close to the “tail” state). Non-monotonic (in s-space) signaling splits the cells into groups. The model shows that different types of signaling may provide different types of cellular patterns. General principles for applying this model to complex cellular structures are discussed.
  PubDate: 2022-12-20
  DOI: 10.1007/s10441-022-09454-2
Correction to: Stem Cells and the Microenvironment: Reciprocity with
Asymmetry in Regenerative Medicine
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  PubDate: 2022-12-09
  DOI: 10.1007/s10441-022-09455-1
Modelling the Effect of Vaccination Program and Inter-state Travel in the
Spread of COVID-19 in Malaysia
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  Abstract: Abstract A modified version of the SEIR model with the effects of vaccination and inter-state movement is proposed to simulate the spread of COVID-19 in Malaysia. A mathematical analysis of the proposed model was performed to derive the basic reproduction number. To enhance the model’s forecasting capabilities, the model parameters were estimated using the Nelder–Mead simplex method by fitting the model outputs to the observed data. Our results showed a good fit between the model outputs and available data, where the model was then able to perform short-term predictions. In line with the rapid vaccination program, our model predicted that the COVID-19 cases in the country would decrease by the end of August. Furthermore, our findings indicated that relaxing travel restrictions from a highly vaccinated region to a low vaccinated region would result in an epidemic outbreak.
  PubDate: 2022-11-17
  DOI: 10.1007/s10441-022-09453-3
Infectious Disease Spreading Fought by Multiple Vaccines Having a
Prescribed Time Effect
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  Abstract: Abstract We propose a framework for the description of the effects of vaccinations on the spreading of an epidemic disease. Different vaccines can be dosed, each providing different immunization times and immunization levels. Differences due to individuals’ ages are accounted for through the introduction of either a continuous age structure or a discrete set of age classes. Extensions to gender differences or to distinguish fragile individuals can also be considered. Within this setting, vaccination strategies can be simulated, tested and compared, as is explicitly described through numerical integrations.
  PubDate: 2022-11-15
  DOI: 10.1007/s10441-022-09452-4
Major Transitions as Groupoid Symmetry-Breaking in Nonergodic Prebiotic,
Biological and Social Information Systems
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  Abstract: Abstract We extend the comparatively simple processes of group symmetry-breaking in physical systems to groupoid/equivalence class phase transitions characterizing adiabatically, piecewise stationary, information transmission in prebiotic, biological, and social phenomena: High vs. Low probability paths \(\rightarrow\) Interior and Exterior Interact \(\rightarrow\) Multiple Interacting Tunable Workspaces Application to nonstationary processes seems possible via generalizations of the symmetry algebra, for example, to semigroupoids. The dynamic probability models explored here can be transformed into statistical tools for the analysis of real-time and other data across a spectrum of important disciplines confronted by biological and other forms of cognition and their dysfunctions.
  PubDate: 2022-10-29
  DOI: 10.1007/s10441-022-09451-5
On the Role of Speed in Technological and Biological Information Transfer
for Computations
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  Abstract: Abstract In all kinds of implementations of computing, whether technological or biological, some material carrier for the information exists, so in real-world implementations, the propagation speed of information cannot exceed the speed of its carrier. Because of this limitation, one must also consider the transfer time between computing units for any implementation. We need a different mathematical method to consider this limitation: classic mathematics can only describe infinitely fast and small computing system implementations. The difference between mathematical handling methods leads to different descriptions of the computing features of the systems. The proposed handling also explains why biological implementations can have lifelong learning and technological ones cannot. Our conclusion about learning matches published experimental evidence, both in biological and technological computing.
  PubDate: 2022-10-26
  DOI: 10.1007/s10441-022-09450-6
Stochastic Modeling and Forecasting of Covid-19 Deaths: Analysis for the
Fifty States in the United States
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  Abstract: Abstract In this work, we study and analyze the aggregate death counts of COVID-19 reported by the United States Centers for Disease Control and Prevention (CDC) for the fifty states in the United States. To do this, we derive a stochastic model describing the cumulative number of deaths reported daily by CDC from the first time Covid-19 death is recorded to June 20, 2021 in the United States, and provide a forecast for the death cases. The stochastic model derived in this work performs better than existing deterministic logistic models because it is able to capture irregularities in the sample path of the aggregate death counts. The probability distribution of the aggregate death counts is derived, analyzed, and used to estimate the count’s per capita initial growth rate, carrying capacity, and the expected value for each given day as at the time this research is conducted. Using this distribution, we estimate the expected first passage time when the aggregate death count is slowing down. Our result shows that the expected aggregate death count is slowing down in all states as at the time this analysis is conducted (June 2021). A formula for predicting the end of Covid-19 deaths is derived. The daily expected death count for each states is plotted as a function of time. The probability density function for the current day, together with the forecast and its confidence interval for the next four days, and the root mean square error for our simulation results are estimated.
  PubDate: 2022-09-16
  DOI: 10.1007/s10441-022-09449-z
COVID-19 Adaptive Humoral Immunity Models: Weakly Neutralizing Versus
Antibody-Disease Enhancement Scenarios
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  Abstract: Abstract The interplay between the virus, infected cells and immune responses to SARS-CoV-2 is still under debate. By extending the basic model of viral dynamics, we propose here a formal approach to describe neutralisation versus weak (or non-)neutralisation scenarios and compare them with the possible effects of antibody-dependent enhancement (ADE). The theoretical model is consistent with the data available in the literature; we show that both weakly neutralising antibodies and ADE can result in final viral clearance or disease progression, but that the immunodynamics are different in each case. As a significant proportion of the world’s population is already naturally immune or vaccinated, we also discuss the implications for secondary infections after vaccination or in the presence of immune system dysfunctions.
  PubDate: 2022-08-13
  DOI: 10.1007/s10441-022-09447-1
Stem Cells and the Microenvironment: Reciprocity with Asymmetry in
Regenerative Medicine
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  Abstract: Abstract Much of the current research in regenerative medicine concentrates on stem-cell therapy that exploits the regenerative capacities of stem cells when injected into different types of human tissues. Although new therapeutic paths have been opened up by induced pluripotent cells and human mesenchymal cells, the rate of success is still low and mainly due to the difficulties of managing cell proliferation and differentiation, giving rise to non-controlled stem cell differentiation that ultimately leads to cancer. Despite being still far from becoming a reality, these studies highlight the role of physical and biological constraints (e.g., cues and morphogenetic fields) placed by tissue microenvironment on stem cell fate. This asks for a clarification of the coupling of stem cells and microenvironmental factors in regenerative medicine. We argue that extracellular matrix and stem cells have a causal reciprocal and asymmetric relationship in that the 3D organization and composition of the extracellular matrix establish a spatial, temporal, and mechanical control over the fate of stem cells, which enable them to interact and control (as well as be controlled by) the cellular components and soluble factors of microenvironment. Such an account clarifies the notions of stemness and stem cell regeneration consistently with that of microenvironment.
  PubDate: 2022-08-13
  DOI: 10.1007/s10441-022-09448-0
Inferential Pluralism in Causal Reasoning from Randomized Experiments
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  Abstract: Abstract Causal pluralism can be defended not only in respect to causal concepts and methodological guidelines, but also at the finer-grained level of causal inference from a particular source of evidence for causation. An argument for this last variety of pluralism is made based on an analysis of causal inference from randomized experiments (RCTs). Here, the causal interpretation of a statistically significant association can be established via multiple paths of reasoning, each relying on different assumptions and providing distinct elements of information in favour of a causal interpretation.
  PubDate: 2022-08-13
  DOI: 10.1007/s10441-022-09446-2
Modelling the Influence of Climatic Factors on the Population Dynamics of
Radopholus Similis: Banana-Plantain Pest
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  Abstract: Abstract Radopholus Similis (R. Similis) or burrowing nematode, is one of the most damaging and widespread nematodes attacking bananas, causing toppling or blackhead disease. A mathematical model for the population dynamics of R. Similis is considered, with the aim of investigating the impact of climatic factors on the growth of R. Similis. In this paper, based on the life cycle of R. Similis, we first propose a mathematical model to study and control the population dynamics of this banana pest. We show also how control terms based on biological and chemical controls can be integrated to reduce the population of R. Similis within banana-plantain roots. Sensitivity analysis was performed to show the most important parameters of the model. We present the theoretical analysis of the model. More precisely, we derive a threshold parameter \({\mathcal{N}}_0\) , called the basic offspring number and show that the trivial equilibrium is globally asymptotically stable whenever \({\mathcal{N}}_0\le 1\) , while when \({\mathcal{N}}_0> 1\) , the non trivial equilibrium is globally asymptotically stable. After, we extend the proposed model by taking account climatic factors that influence the growth of this pest. Biological and chemical controls are now introduced through impulsive equations. Threshold and equilibria are obtained and global stabilities have been studied. The theoretical results are supported by numerical simulations. Numerical results of model with biological and chemical controls reveal that biological methods are more effective than chemical methods. We also found that the month February is the best time to apply these controls.
  PubDate: 2022-07-08
  DOI: 10.1007/s10441-022-09444-4
An Epidemic Model with Pro and Anti-vaccine Groups
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  Abstract: Abstract Here, an epidemiological model considering pro and anti-vaccination groups is proposed and analyzed. In this model, susceptible individuals can migrate between these two groups due to the influence of false and true news about safety and efficacy of vaccines. From this model, written as a set of three ordinary differential equations, analytical expressions for the disease-free steady state, the endemic steady state, and the basic reproduction number are derived. It is analytically shown that low vaccination rate and no influx to the pro-vaccination group have similar impacts on the long-term amount of infected individuals. Numerical simulations are performed with parameter values of the COVID-19 pandemic to illustrate the analytical results. The possible relevance of this work is discussed from a public health perspective.
  PubDate: 2022-07-08
  DOI: 10.1007/s10441-022-09443-5
Integration of Heterogeneous Biological Data in Multiscale Mechanistic
Model Calibration: Application to Lung Adenocarcinoma
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  Abstract: Abstract Mechanistic models are built using knowledge as the primary information source, with well-established biological and physical laws determining the causal relationships within the model. Once the causal structure of the model is determined, parameters must be defined in order to accurately reproduce relevant data. Determining parameters and their values is particularly challenging in the case of models of pathophysiology, for which data for calibration is sparse. Multiple data sources might be required, and data may not be in a uniform or desirable format. We describe a calibration strategy to address the challenges of scarcity and heterogeneity of calibration data. Our strategy focuses on parameters whose initial values cannot be easily derived from the literature, and our goal is to determine the values of these parameters via calibration with constraints set by relevant data. When combined with a covariance matrix adaptation evolution strategy (CMA-ES), this step-by-step approach can be applied to a wide range of biological models. We describe a stepwise, integrative and iterative approach to multiscale mechanistic model calibration, and provide an example of calibrating a pathophysiological lung adenocarcinoma model. Using the approach described here we illustrate the successful calibration of a complex knowledge-based mechanistic model using only the limited heterogeneous datasets publicly available in the literature.
  PubDate: 2022-07-07
  DOI: 10.1007/s10441-022-09445-3
Bridging Theories for Ecosystem Stability Through Structural Sensitivity
Analysis of Ecological Models in Equilibrium
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  Abstract: Abstract Ecologists are challenged by the need to bridge and synthesize different approaches and theories to obtain a coherent understanding of ecosystems in a changing world. Both food web theory and regime shift theory shine light on mechanisms that confer stability to ecosystems, but from different angles. Empirical food web models are developed to analyze how equilibria in real multi-trophic ecosystems are shaped by species interactions, and often include linear functional response terms for simple estimation of interaction strengths from observations. Models of regime shifts focus on qualitative changes of equilibrium points in a slowly changing environment, and typically include non-linear functional response terms. Currently, it is unclear how the stability of an empirical food web model, expressed as the rate of system recovery after a small perturbation, relates to the vulnerability of the ecosystem to collapse. Here, we conduct structural sensitivity analyses of classical consumer-resource models in equilibrium along an environmental gradient. Specifically, we change non-proportional interaction terms into proportional ones, while maintaining the equilibrium biomass densities and material flux rates, to analyze how alternative model formulations shape the stability properties of the equilibria. The results reveal no consistent relationship between the stability of the original models and the proportionalized versions, even though they describe the same biomass values and material flows. We use these findings to critically discuss whether stability analysis of observed equilibria by empirical food web models can provide insight into regime shift dynamics, and highlight the challenge of bridging alternative modelling approaches in ecology and beyond.
  PubDate: 2022-06-23
  DOI: 10.1007/s10441-022-09441-7