Theory in Biosciences最新文献

In this work, we formulate the following question: How the distribution of aminoacyl-tRNA synthetases (aaRSs) went from an ancestral bidirectional gene (mirror symmetry) to the symmetrical distribution of aaRSs in a six-dimensional hypercube of the Standard Genetic Code (SGC)? We assume a primeval RNY code, two Extended Genetic RNA codes type 1 and 2, and the SGC. We outline the types of symmetries of the distribution of aaRSs in each code. The symmetry groups of aaRSs in each code are described, until the symmetries of the SGC display a mirror symmetry. Considering both Extended RNA codes the 20 aaRSs were already present before the Last Universal Ancestor. These findings reveal intricacies in the diversification of aaRSs accompanied by the evolution of the genetic code.

We consider a modified SIR model with a four-dimensional system of ordinary differential equations to consider the influence of a limited isolation capacity on the final epidemic size defined as the total number of individuals who experienced the disease at the end of an epidemic season. We derive the necessary and sufficient condition that the isolation reaches the capacity in a finite time on the way of the epidemic process, and show that the final epidemic size is monotonically decreasing in terms of the isolation capacity. We find further that the final epidemic size could have a discontinuous change at the critical value of isolation capacity below which the isolation reaches the capacity in a finite time. Our results imply that the breakdown of isolation with a limited capacity would cause a drastic increase of the epidemic size. Insufficient capacity of the isolation could lead to an unexpectedly severe epidemic situation, while such a severity would be avoidable with the sufficient isolation capacity.

In this paper a Feynman-type path integral control approach is used for a recursive formulation of a health objective function subject to a fatigue dynamics, a forward-looking stochastic multi-risk susceptible-infective-recovered (SIR) model with risk-group's Bayesian opinion dynamics toward vaccination against COVID-19. My main interest lies in solving a minimization of a policy-maker's social cost which depends on some deterministic weight. I obtain an optimal lock-down intensity from a Wick-rotated Schrödinger-type equation which is analogous to a Hamiltonian-Jacobi-Bellman (HJB) equation. My formulation is based on path integral control and dynamic programming tools facilitates the analysis and permits the application of algorithm to obtain numerical solution for pandemic control model.

In this article, we study the dynamical properties of susceptible-vaccinated-infected-susceptible (SVIS) epidemic system with saturated incidence rate and vaccination strategies. By constructing the suitable Lyapunov function, we examine the existence and uniqueness of the stochastic system. With the help of Khas'minskii theory, we set up a critical value [Formula: see text] with respect to the basic reproduction number [Formula: see text] of the deterministic system. A unique ergodic stationary distribution is investigated under the condition of [Formula: see text]. In the epidemiological study, the ergodic stationary distribution represents that the disease will persist for long-term behavior. We focus for developing the general three-dimensional Fokker-Planck equation using appropriate solving theories. Around the quasi-endemic equilibrium, the probability density function of the stochastic system is analyzed which is the main theme of our study. Under [Formula: see text], both the existence of ergodic stationary distribution and density function can elicit all the dynamical behavior of the disease persistence. The condition of disease extinction of the system is derived. For supporting theoretical study, we discuss the numerical results and the sensitivities of the biological parameters. Results and conclusions are highlighted.

Autosomal dominant diseases typically have an age-related onset. Here, I focus on genetic prion disease (gPrD), caused by various mutations in the PRNP gene. While gPrD typically occurs at or after middle age, there can be considerable variability in the specific age of onset. This variability can occur among patients with the same PRNP mutation; in some cases, these differences occur not only between families but even within the same family. It is not known why gPrD onset is typically delayed for decades when the causative mutation is present from birth. Mouse models of gPrD manifest disease; however, unlike human gPrD, which typically takes decades to manifest, mouse models exhibit disease within months. Therefore, the time to onset of prion disease is proportional to species lifespan; however, it is not known why this is the case. I hypothesize that the initiation of gPrD is strongly influenced by the process of aging; therefore, disease onset is related to proportional functional age (e.g., mice vs. humans). I propose approaches to test this hypothesis and discuss its significance with respect to delaying prion disease through suppression of aging.

In biological processes involving gene networks, genes regulate other genes that determine the phenotypic traits. Gene regulation plays an important role in evolutionary dynamics. In a genetic algorithm, a trans-gene regulatory mechanism was shown to speed up adaptation and evolution. Here, we examine the effect of cis-gene regulation on an adaptive system. The model is haploid. A chromosome is partitioned into regulatory loci and structural loci. The regulatory genes regulate the expression and functioning of structural genes via the cis-elements in a probabilistic manner. In the simulation, the change in the allele frequency, the mean population fitness and the efficiency of phenotypic selection are monitored. Cis-gene regulation increases adaption and accelerates the evolutionary process in comparison with the case involving absence of gene regulation. Some special features of the simulation results are as follows. A low ratio of regulatory loci and structural loci gives higher adaptation for fixed total number of loci. Plasticity is advantageous beyond a threshold value. Adaptation is better for large number of total loci when the ratio of regulatory loci to structural loci is one. However, it reaches a saturation beyond which the increase in the total loci is not advantageous. Efficiency of the phenotypic selection is higher for larger value of the initial plasticity.

In this study, we proposed a biological model explaining the progress of autoimmune activation along different stages of systemic lupus erythematosus (SLE). For any upcoming stage of SLE, any new component is introduced, when it is added to the model. Particularly, the interaction of mesenchymal stem cells, with the components of the model, is specified in a way that both the inflammatory and anti-inflammatory functions of these cells would be covered. The biological model is then recapitulated to a model with less complexity that explains the main features of the problem. Later, a 7th-order mathematical model for SLE is proposed, based on this simplified model. Finally, the range of validity of the proposed mathematical model was assessed. For this purpose, we simulated the model and analyzed the simulation results in case of some known behaviors of the disease, such as tolerance breach, the appearance of systemic inflammation, development of clinical signs, and occurrence of flares and improvements. The model was able to reproduce these events, qualitatively.

Recent results have shown that the human malaria-resistant hemoglobin S mutation originates de novo more frequently in the gene and in the population where it is of adaptive significance, namely, in the hemoglobin subunit beta gene compared to the nonresistant but otherwise identical 20A[Formula: see text]T mutation in the hemoglobin subunit delta gene, and in sub-Saharan Africans, who have been subject to intense malarial pressure for many generations, compared to northern Europeans, who have not. This finding raises a fundamental challenge to the traditional notion of accidental mutation. Here, we address this finding with the replacement hypothesis, according to which preexisting genetic interactions can lead directly and mechanistically to mutations that simplify and replace them. Thus, an evolutionary process under selection can gradually hone in on interactions of importance for the currently evolving adaptations, from which large-effect mutations follow that are relevant to these adaptations. We exemplify this hypothesis using multiple types of mutation, including gene fusion mutations, gene duplication mutations, A[Formula: see text]G mutations in RNA-edited sites and transcription-associated mutations, and place it in the broader context of a system-level view of mutation origination called interaction-based evolution. Potential consequences include that similarity of mutation pressures may contribute to parallel evolution in genetically related species, that the evolution of genome organization may be driven by mutational mechanisms, that transposable element movements may also be explained by replacement, and that long-term directed mutational responses to specific environmental pressures are possible. Such mutational phenomena need to be further tested by future studies in natural and artificial settings.

In animal species with separate sexes, abnormal individuals with a mix of phenotypically male and phenotypically female body parts are generally indicated as gynandromorphs, whereas individuals with intermediate sexual phenotypic traits are generally indicated as intersexes. However, this distinction, clear as it may seem, is neither universally agreed upon, nor free of critical issues. In consideration of the role of sex anomalies in understanding normal development, we reassess these phenomena of abnormal sexual development, taking into consideration the more recent advances in the study of sex determination and sexual differentiation. We argue that a distinction between gynandromorphism and intersexuality, although useful for descriptive purposes, is not always possible or sensible. We discuss the conceptual and terminological intricacies of the literature on this subject and provide reasons for largely, although not strictly, preferring a terminology based on descriptive rather than causal morphology, that is, on the observed phenotypic patterns rather on the causal process behind them.

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.