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The classical theory of descent with modification by means of natural selection had no mother, but did have two English fathers, Charles Darwin (1809-1882) and Alfred Russel Wallace (1823-1913). In 1858, the Linnean Society of London published two contributions of these naturalists and acknowledged both authors as the proponents of a novel hypothesis on the driving force of organismic evolution. In the present report the most important sections of the Darwin-Wallace papers are summarized. This close reading of both publications reveals six striking differences in emphasis: Darwin and Wallace did not propose identical ideas. The species definitions of both authors are described and the further development of the concept of natural selection in wild populations is reviewed. It is shown that the contributions of A.R. Wallace, who died 90 years ago, are more significant than usually acknowledged. I conclude that natural selection's lesser known co-discoverer should be regarded as one of the most important pioneers of evolutionary biology, whose original contributions are underestimated by most contemporary scientists. [ABSTRACT FROM AUTHOR]

The phenomenon of near death and dying experiences has been both of popular interest and of scientific speculation. However, the reality of mental perception at the point of death is currently a subjective experience and has not been formally evaluated. While postmortem gene expression, even in humans, has been evaluated, restoration of postmortem brain activity has heretofore only been attempted in animal models, at the molecular and cellular levels. Meanwhile, progress has been made to translate brain activity of living humans into speech and images. This paper proposes two inter-related thought experiments. First, assuming progress and refinement of the technology of translating human brain activity into interpretable speech and images, can an objective analysis of death experiences be obtained by utilizing these technologies on dying humans? Second, can human brain function be revived postmortem and, if so, can the relevant technologies be utilized for communication with (recently) deceased individuals? In this paper, these questions are considered and possible implications explored. [ABSTRACT FROM AUTHOR]

The origins of innovation in science are typically understood using historical narratives that tend to be focused on small sets of influential authors, an approach that is rigorous but limited in scope. Here, we develop a framework for rigorously identifying innovation across an entire scientific field through automated analysis of a corpus of over 6000 documents that includes every paper published in the field of evolutionary medicine. This comprehensive approach allows us to explore statistical properties of innovation, asking where innovative ideas tend to originate within a field's pre-existing conceptual framework. First, we develop a measure of innovation based on novelty and persistence, quantifying the collective acceptance of novel language and ideas. Second, we study the field's conceptual landscape through a bibliographic coupling network. We find that innovations are disproportionately more likely in the periphery of the bibliographic coupling network, suggesting that the relative freedom allowed by remaining unconnected with well-established lines of research could be beneficial to creating novel and lasting change. In this way, the emergence of collective computation in scientific disciplines may have robustness–adaptability trade-offs that are similar to those found in other biosocial complex systems. [ABSTRACT FROM AUTHOR]

To what extent do simultaneous innovations occur and are independently from each other? In this paper we use a novel persistent keyword framework to systematically identify innovations in a large corpus containing academic papers in evolutionary medicine between 2007 and 2011. We examine whether innovative papers occurring simultaneously are independent from each other by evaluating the citation and co-authorship information gathered from the corpus metadata. We find that 19 out of 22 simultaneous innovative papers do, in fact, occur independently from each other. In particular, co-authors of simultaneous innovative papers are no more geographically concentrated than the co-authors of similar non-innovative papers in the field. Our result suggests producing innovative work draws from a collective knowledge pool, rather than from knowledge circulating in distinct localized collaboration networks. Therefore, new ideas can appear at multiple locations and with geographically dispersed co-authorship networks. Our findings support the perspective that simultaneous innovations are the outcome of collective behavior. [ABSTRACT FROM AUTHOR]

This paper addresses the relationship between information and structure of the genetic code. The code has two puzzling anomalies: First, when viewed as 64 sub-cubes of a 4 × 4 × 4 cube, the codons for serine (S) are not contiguous, and there are amino acid codons with zero redundancy, which goes counter to the objective of error correction. To make sense of this, the paper shows that the genetic code must be viewed not only on stereochemical, co-evolution, and error-correction considerations, but also on two additional factors of significance to natural systems, that of an information-theoretic dimensionality of the code data, and the principle of maximum entropy. One implication of non-integer dimensionality associated with data dimensions is self-similarity to different scales, and it is shown that the genetic code does satisfy this property, and it is further shown that the maximum entropy principle operates through the scrambling of the elements in the sense of maximum algorithmic information complexity, generated by an appropriate exponentiation mapping. It is shown that the new considerations and the use of maximum entropy transformation create new constraints that are likely the reasons for the non-uniform codon groups and codons with no redundancy. [ABSTRACT FROM AUTHOR]

There is an old attempt to divide the sciences into sciences of laws and the historical sciences. More recently, John Beatty has drawn the distinction so that biology is a historical science and urged that there are no genuinely biological laws. This paper shows that there are indeed biological laws, specifically statistical ones, notably in evolutionary theory. Moreover, all or almost all other areas of biology involve laws as well. Even history involves laws. Finally, the paper shows that this pervasiveness of laws is compatible with the most basic commitments of those who, like Beatty, would claim that biology is only historical. [ABSTRACT FROM AUTHOR]

The bio-cell cycle is controlled by a complex biochemical network of signaling pathways. Modeling such challenging networks accurately is imperative for the understanding of their detailed dynamical behavior. In this paper, we construct, analyze, and verify a hybrid Petri net (HPN) model of a complex biochemical network that captures the role of an important protein (namely p53) in deciding the fate of the cell. We model the behavior of the cell nucleus and cytoplasm as two stochastic and continuous Petri nets, respectively, combined together into a single HPN. We use simulative model checking to verify three different properties that capture the dynamical behavior of p53 protein with respect to the intensity of the ionizing radiation (IR) to which the cell is exposed. For each IR dose, 1000 simulation runs are carried out to verify each property. Our verification results showed that the fluctuations in p53, which relies on IR intensity, are compatible with the findings of the preceding simulation studies that have previously examined the role of p53 in cell fate decision. [ABSTRACT FROM AUTHOR]

What is the role of consciousness in volition and decision-making? Are our actions fully determined by brain activity preceding our decisions to act, or can consciousness instead affect the brain activity leading to action? This has been much debated in philosophy, but also in science since the famous experiments by Libet in the 1980s, where the current most common interpretation is that conscious free will is an illusion. It seems that the brain knows, up to several seconds in advance what "you" decide to do. These studies have, however, been criticized, and alternative interpretations of the experiments can be given, some of which are discussed in this paper. In an attempt to elucidate the processes involved in decision-making (DM), as an essential part of volition, we have developed a computational model of relevant brain structures and their neurodynamics. While DM is a complex process, we have particularly focused on the amygdala and orbitofrontal cortex (OFC) for its emotional, and the lateral prefrontal cortex (LPFC) for its cognitive aspects. In this paper, we present a stochastic population model representing the neural information processing of DM. Simulation results seem to confirm the notion that if decisions have to be made fast, emotional processes and aspects dominate, while rational processes are more time consuming and may result in a delayed decision. Finally, some limitations of current science and computational modeling will be discussed, hinting at a future development of science, where consciousness and free will may add to chance and necessity as explanation for what happens in the world. [ABSTRACT FROM AUTHOR]

The multilevel model of behavioral selection (MLBS) by Borgstede and Eggert (Behav Process 186:104370. 10.1016/j.beproc.2021.104370, 2021) provides a formal framework that integrates reinforcement learning with natural selection using an extended Price equation. However, the MLBS is so far only formulated for homogeneous populations, thereby excluding all sources of variation between individuals. This limitation is of primary theoretical concern because any application of the MLBS to real data requires to account for variation between individuals. In this paper, I extend the MLBS to account for inter-individual variation by dividing the population into homogeneous sub-populations and including class-specific reproductive values as weighting factors for an individual's evolutionary fitness. The resulting formalism closes the gap between the theoretical underpinnings of behavioral selection and the application of the theory to empirical data, which naturally includes inter-individual variation. Furthermore, the extended MLBS is used to establish an explicit connection between the dynamics of learning and the maximization of individual fitness. These results expand the scope of the MLBS as a general theoretical framework for the quantitative analysis of learning and evolution. [ABSTRACT FROM AUTHOR]

In this paper, a new mathematical model that describes the dynamics of the within-host COVID-19 epidemic is formulated. We show the stochastic dynamics of Target-Latent-Infected-Virus free within the human body with discrete delay and noise. Positivity and uniqueness of the solutions are established. Our study shows the extinction and persistence of the disease inside the human body through the stability analysis of the disease-free equilibrium E 0 and the endemic equilibrium E ∗ , respectively. Moreover, we show the impact of delay tactics and noise on the extinction of the disease. The most interesting result is even if the deterministic system is inevitably pandemic at a specific point, extinction will become possible in the stochastic version of our model. [ABSTRACT FROM AUTHOR]

In this paper we are concerned with how aggregated outcomes of individual behaviours, during interactions with other individuals (games) or with environmental factors, determine the vital rates constituting the growth rate of the population. This approach needs additional elements, namely the rates of event occurrence (interaction rates). Interaction rates describe the distribution of the interaction events in time, which seriously affects the population dynamics, as is shown in this paper. This leads to the model of a population of individuals playing different games, where focal game affected by the considered trait can be extracted from the general model, and the impact on the dynamics of other events (which is not neutral) can be described by an average background fertility and mortality. This leads to a distinction between two types of background fitness, strategically neutral elements of the focal games (correlated with the focal game events) and the aggregated outcomes of other interactions (independent of the focal game). The new approach is useful for clarification of the biological meaning of concepts such as weak selection. Results are illustrated by a Hawk-Dove example. [ABSTRACT FROM AUTHOR]

In this paper, we study the global properties of a computer virus propagation model. It is, interesting to note that the classical method of Lyapunov functions combined with the Volterra-Lyapunov matrix properties, can lead to the proof of the endemic global stability of the dynamical model characterizing the spread of computer viruses over the Internet. The analysis and results presented in this paper make building blocks towards a comprehensive study and deeper understanding of the fundamental mechanism in computer virus propagation model. A numerical study of the model is also carried out to investigate the analytical results. [ABSTRACT FROM AUTHOR]

Breast cancer stem cells (BCSCs) with the ability to self-renew and differentiate have been identified in primary breast cancer tissues and cell lines. The BCSCs are often resistant to traditional radiation and/or chemotherapies. Previous studies have also shown that successful therapy must eradicate cancer stem cells. The purpose of this paper is to develop a mathematical model with self-feedback mechanism to illustrate the issues regarding the difficulties of absolutely eliminating a breast cancer. In addition, we introduce the mechanism of the epithelial-mesenchymal transition (EMT) to investigate the influence of EMT on the effects of breast cancer growth and treatment. Results indicate that the EMT mechanism facilitates the growth of breast cancer and makes breast cancer more difficult to be cured. Therefore, targeting the signals involved in EMT can halt tumor progression in breast cancer. Finally, we apply the experimental data to carry out numerical simulations and validate our theoretical conclusions. [ABSTRACT FROM AUTHOR]

This paper is aimed at demonstrating that some geometrical and topological transformations and operations serve not only as promoters of many specific genetic and cellular events in multicellular living organisms, but also as initiators of the organization and regulation of their functions. Thus, changes in the form and structure of macromolecular and cellular systems must be directly associated to their functions. There are specific classes of enzymes that manipulate the geometry and topology of complex DNA–protein structures, and thereby they perform many important cellular processes, including segregation of daughter chromosomes, gene regulation, and DNA repair. We argue that form has an organizing power, hence a causal action, in the sense that it enables to induce functional events during different biological processes, at the supramolecular, cellular, and organismal levels of organization. Clearly, topological forms must be matched with specific kinetic and dynamical parameters to have a functional effectiveness in living systems. This effectiveness is remarkably apparent, to give an example, in the regulation of the genome functions and in cell activity. In more general terms, we try to show that the conformational plasticity of biological systems depends on different kinds of topological manipulations performed by specific families of enzymes. In doing so, they catalyze all those spatial and dynamical changes of biological structures that are suitable for the functions to be acted by the organism. [ABSTRACT FROM AUTHOR]

In this paper, we understand the emergence of life as a pure individuation process. Individuation already occurs in open thermodynamics systems near equilibrium. We understand such open systems, as already recursively characterized (R1) by the relation between their internal properties, and their boundary conditions. Second, global properties emerge in such physical systems. We interpret this change as the fact that their structure is the recursive result of their operations (R2). We propose a simulation of the emergence of life in Earth by a mapping (R) through which (R1R2) operators are applied to themselves, so that RN = (R1R2)N. We suggest that under specific thermodynamic (open systems out of equilibrium) and chemical conditions (autocatalysis, kinetic dynamic stability), this mapping can go up to a limit characterized by a fixed-point equation: R = ϕ 1 ϕ 2 R . In this equation, ( ϕ 1 ) symbolizes a regime of permanent resonance characterizing the biosphere, as open from inside, by the recursive differential relation between the biosphere and all its holobionts. As such the biosphere is closed on itself as a pure differential entity. ( ϕ 2 ) symbolizes the regime of permanent change characterizing the emergence of evolution in the biosphere. As such the biosphere is closed on itself, by the principle of descent with modifications, and by the fact that every holobiont evolves in a niche, while evolving with it. [ABSTRACT FROM AUTHOR]

A mathematical model for the quantitative analysis of the interaction between cancer cells and cell-mediated immune system with two discrete-time delays, considering the role of antibodies, is studied in this paper. The model is analyzed both analytically and numerically to understand the dynamics of interaction delay and proliferation enhancement effect delay in the eradication of cancer. Hopf bifurcation occurs when one-time delay crosses the critical value in the absence of the other. It is also observed that as we increase any of the delays, it will increase the cancer burden. The analysis shows that a cancer-free state cannot be obtained solely by the killing rate of cytotoxic T-lymphocytes, but humoral response in combination with cell-mediated immune responses plays an important role to eradicate cancer. [ABSTRACT FROM AUTHOR]

Fungi show a high degree of morphological convergence. Regarded for a long time as an obstacle for phylogenetic studies, homoplasy has also been proposed as a source of information about underlying morphogenetic patterning mechanisms. The "local-activation and long-range inhibition principle" (LALIP), underlying the famous reaction–diffusion model proposed by Alan Turing in 1952, appears to be one of the universal phenomena that can explain the ontogenetic origin of seriate patterns in living organisms. Reproductive structures of fungi in the class Agaricomycetes show a highly periodic structure resulting in, for example, poroid, odontoid, lamellate or labyrinthic hymenophores. In this paper, we claim that self-organized patterns might underlie the basic ontogenetic processes of these structures. Simulations based on LALIP-driven models and covering a wide range of parameters show an absolute mutual correspondence with the morphospace explored by extant agaricomycetes. This could not only explain geometric particularities but could also account for the limited possibilities displayed by hymenial configurations, thus making homoplasy a direct consequence of the limited morphospace resulting from the proposed patterning dynamics. [ABSTRACT FROM AUTHOR]

In this paper, we develop the mathematical structure of the Wright-Fisher model for evolution of the relative frequencies of two alleles at a diploid locus under random genetic drift in a population of fixed size in its simplest form, that is, without mutation or selection. We establish a new concept of a global solution for the diffusion approximation (Fokker-Planck equation), prove its existence and uniqueness and then show how one can easily derive all the essential properties of this random genetic drift process from our solution. Thus, our solution turns out to be superior to the local solution constructed by Kimura. [ABSTRACT FROM AUTHOR]

Comprehending life history of migratory fish, onset of migration in particular, is a key biological and ecological research topic that still has not been clarified. In this paper, we propose a simple mathematical model for the onset of fish migration in the context of a stochastic optimal stopping theory, which is a new attempt to our knowledge. Finding the criteria of the onset of migration reduces to solving a variational inequality of a degenerate elliptic type. As a first step of the new mathematical modeling, mathematical and numerical analyses with particular emphasis on whether the model is consistent with the past observation results of fish migration are examined, demonstrating reasonable agreement between the theory and observation results. The present mathematical model thus potentially serves as a simple basis for analyzing onset of fish migration. [ABSTRACT FROM AUTHOR]

Research on symbiotic communities (microbiomes) of multicellular organisms seems to be changing our understanding of how species of plants and animals have evolved over millions of years. The quintessence of these discoveries is the emergence of the hologenome theory of evolution, founded on the concept that a holobiont (a host along with all of its associated symbiotic microorganisms) acts a single unit of selection in the process of evolution. Although the hologenome theory has become very popular among certain scientific circles, its principles are still being debated. In this paper, we argue, firstly, that only a very small number of symbiotic microorganisms are sufficiently integrated into multicellular organisms to act in concert with them as units of selection, thus rendering claims that holobionts are units of selection invalid. Secondly, even though holobionts are not units of selection, they can still constitute genuine units from an evolutionary perspective, provided we accept certain constraints: mainly, they should be considered units of co-operation. Thirdly, we propose a reconciliation of the role of symbiotic microorganisms with the theory of speciation through the use of a developed framework. Mainly, we will argue that, in order to understand the role of microorganisms in the speciation of multicellular organisms, it is not necessary to consider holobionts units of selection; it is sufficient to consider them units of co-operation. [ABSTRACT FROM AUTHOR]

In the fight against the COVID-19 pandemic, many brilliant results have been achieved, but the thermodynamics of the novel SARS-CoV-2 coronavirus has been completely neglected. This is a serious systematic error, which can compromise the results of the entire pandemic virus SARS-CoV-2 research. In the present work, we therefore study the thermodynamics of SARS-CoV-2 in its environment, from air to endosome and endosome-independent cell entry pathways. In the study of the thermodynamics of the new coronavirus SARS-CoV-2 in air, the presence of pollen, bacteria, other viruses, spores, dust, but more particularly, that of nanoparticles of health interest at the same scale threshold as the spike proteins of the pandemic virus, such as particulate matter, cannot be neglected. This work therefore starts from a comparative study of the air environments in China and Italy, the first countries affected by the infection. Currently, a correlation between the spread of infection and pollution is still very controversial. But our paper is not concerned with this. We propose some methodological notes which lead us to the formulation of a general mathematical apparatus (an energy landscape theory), suitable to explain at the molecular level the energetic configurations of the quasi-species of the pandemic virus SARS-CoV-2 in its environment. We focus on complexes between the viral particle and other objects in its environment at the scale threshold of the spikes of the viral particle. Then, we wondered if such complexes can lead to the generation of more aggressive viral variants and how to predict their populations and energy configurations, in order to plan an adequate prophylaxis. [ABSTRACT FROM AUTHOR]

Self-complementary circular codes are involved in pairing genetic processes. A maximal C3 self-complementary circular code X of trinucleotides was identified in genes of bacteria, archaea, eukaryotes, plasmids and viruses (Michel in Life 7(20):1-16 2017, J Theor Biol 380:156-177, 2015; Arquès and Michel in J Theor Biol 182:45-58 1996). In this paper, self-complementary circular codes are investigated using the graph theory approach recently formulated in Fimmel et al. (Philos Trans R Soc A 374:20150058, 2016). A directed graph G(X) associated with any code X mirrors the properties of the code. In the present paper, we demonstrate a necessary condition for the self-complementarity of an arbitrary code X in terms of the graph theory. The same condition has been proven to be sufficient for codes which are circular and of large size ∣X∣≥18 trinucleotides, in particular for maximal circular codes (∣X∣=20 trinucleotides). For codes of small-size ∣X∣≤16 trinucleotides, some very rare counterexamples have been constructed. Furthermore, the length and the structure of the longest paths in the graphs associated with the self-complementary circular codes are investigated. It has been proven that the longest paths in such graphs determine the reading frame for the self-complementary circular codes. By applying this result, the reading frame in any arbitrary sequence of trinucleotides is retrieved after at most 15 nucleotides, i.e., 5 consecutive trinucleotides, from the circular code X identified in genes. Thus, an X motif of a length of at least 15 nucleotides in an arbitrary sequence of trinucleotides (not necessarily all of them belonging to X) uniquely defines the reading (correct) frame, an important criterion for analyzing the X motifs in genes in the future. [ABSTRACT FROM AUTHOR]

In this paper, the schooling behavior of prey fish population in a predator–prey interaction is investigated. By taking an economical interest which can be elaborated by the presence of nonselective harvesting into consideration, we studied the dynamical behavior. The existence, positivity and boundedness of solution have been established. The analysis of the equilibrium states is presented by studying the local and the global stability. The possible types of local bifurcation that the system can undergoes are discussed. The effect of fishing effort on the evolution of the species is examined. Further, by using Pontryagin's maximum principle a proper management strategy has been used for avoiding the extinction of the considered species and maximizing the benefits. For the validation of the theoretical result, several of graphical representations have been used. [ABSTRACT FROM AUTHOR]

The outbreak of coronavirus COVID-19 is spreading at an unprecedented rate to the human populations and taking several thousands of life all over the world. Scientists are trying to map the pattern of the transmission of coronavirus (SARS-CoV-2). Many countries are in the phase of lockdown in the globe. In this paper we predict about the effect of coronavirus COVID-19 and give a sneak peak when it will reduce the transmission rate in the world via mathematical modelling. In this research work our study is based on extensions of the well-known susceptible-exposed-infected-recovered (SEIR) family of compartmental models and later we observe the new model changes into (SEIR) without changing its physical meanings. The stability analysis of the coronavirus depends on changing of its basic reproductive ratio. The progress rate of the virus in the critically infected cases and the recovery rate have major roles to control this epidemic. The impact of social distancing, lockdown of the country, self-isolation, home quarantine and the wariness of global public health system have significant influence on the parameters of the model system that can alter the effect of recovery rates, mortality rates and active contaminated cases with the progression of time in the real world. The prognostic ability of mathematical model is circumscribed as of the accuracy of the available data and its application to the problem. [ABSTRACT FROM AUTHOR]

In 1835, the meaning of the cleavage furrows in the division of frog eggs was the cause of a heated argument between the Italian naturalist Mauro Rusconi and Karl Ernst von Baer. These furrows were first described by Prévost and Dumas (Ann Sci Nat 2:100–121, 129–149, 1824b) who did not realize they cut the egg into separate masses. Rusconi (Développement de la grenouille comune depuis le moment de sa naissance jusque a son état parfait, Giusti, Milano, 1826) hypothesized a connection between the furrows and a peculiar crystallization of the content of the egg which eventually produced elementary molecules as the building blocks of the embryo. von Baer (Arch Anat Phys Wiss Med 6:481–509, 1834) was the first to establish a link between the furrows and an active process of dichotomous division he considered to be the basis for all further development and differentiation. The present paper analyses the theoretical reasons behind these divergent interpretations and focuses attention on their implications for the development of the cell theory and the conceptions of life. Prévost, Dumas and Rusconi interpreted cleavage and the whole embryonic development in the light of eighteenth-century scientific theories and the French materialism of the early nineteenth century, which explained life in terms of ordered molecular movement. Starting from other premises partly rooted in German philosophy von Baer (1834) gave a totally different picture which anticipated the cell theory and modern embryology. [ABSTRACT FROM AUTHOR]