Accurate prediction of epidemic evolution faces challenges such as understanding disease dynamics and inadequate epidemiological data. A recent approach faced these issues by modeling susceptible-infectious-susceptible (SIS) dynamics based on the first two statistical moments. Here, we improve this approach by including finite-size populations and analyzing the stability of the resulting model. Results underscore the influence of uncertainties and population size in the natural history of the epidemic.

Coarse-grain models are essential to understand the biological function of DNA molecules because the length and time scales of the sequence-dependent physical properties of DNA are often beyond the reach of experimental and all-atom computational methods. Simulating coarse-grain models of DNA, e.g. using Langevin dynamics, requires the parametrization of both potential and kinetic energy functions. Many studies have shown that the flexibility (i.e., potential energy) of a DNA molecule depends on its sequence. In contrast, little is known about the sequence-dependence of DNA mass parameters required to model its kinetic energy. In this paper, an algebraic expression is derived for the kinetic energy as a function of linear and angular velocities of each DNA base parameterized by its mass, center of mass, and rotational inertia tensor. The parameters of this function are then approximated from a set of fine-grain molecular dynamics simulations representing all combinations of the four DNA base pairs AT, TA, GC, and CG, in different sequence contexts. Compatibility conditions associated with the assumption of each base being modeled as a rigid body were verified to be good approximations. The kinetic parameters were found to be significantly different between the four G, C, A, and T bases, and to not be dependent on the sequence context. This suggests that the effective kinetic parameters of a DNA base may depend only on the base itself, not on its neighbors.

Using delay differential equations to study mathematical models of Parkinson's disease and Huntington's disease is important to show how important it is for synchronization between basal ganglia loops to work together. We used the delay circuit RLC (resistor, inductor, capacitor) model to show how the direct pathway and the indirect pathway in the basal ganglia excite and inhibit the motor cortex, respectively. A term has been added to the mathematical model without time delay in the case of the hyperdirect pathway. It is proposed to add a non-linear term to adjust the synchronization. We studied Hopf bifurcation conditions for the proposed models. The desynchronization of response times between the direct pathway and the indirect pathway leads to different symptoms of Parkinson's disease. Tremor appears when the response time in the indirect pathway increases at rest. The simulation confirmed that tremor occurs and the motor cortex is in an inhibited state. The direct pathway can increase the time delay in the dopaminergic pathway, which significantly increases the activity of the motor cortex. The hyperdirect pathway regulates the activity of the motor cortex. The simulation showed bradykinesia occurs when we switch from one movement to another that is less exciting for the motor cortex. A decrease of GABA in the striatum or delayed excitation of the substantia nigra from the subthalamus may be a major cause of Parkinson's disease. An increase in the response time delay in one of the pathways results in the chaotic movement characteristic of Huntington's disease.

In clinical endocrinology, it is often assumed that the results of thyroid hormone function tests (TFTs) before total thyroidectomy are considered euthyroid when the circulating concentrations of thyrotropin [TSH] and free thyroxine [FT4] are within the normal reference ranges. Postoperative thyroid replacement therapy with levothyroxine. The aim of L-T4 is to reproduce the preoperative euthyroid condition. Currently, intra-individual changes in the euthyroid set point before and after total thyroidectomy are only partly understood. After total thyroidectomy, a greater postoperative [FT4] than preoperative [FT4] for equivalent euthyroid [TSH] was found, with differences ranging from 3 to 8 pmol/L. This unexplained difference can be explained by the use of a mathematical model of the hypothalamus-pituitary-thyroid (HPT) axis set point theory. In this article, the postoperative HPT euthyroid set point was calculated using a dataset of total thyroidectomized patients with at least three distinguishable postoperative TFTs. The postoperative [TSH] set point was used as a homeostatic reference for the comparison of preoperative TFTs. The preoperative [FT4] value was equal to the postoperative [FT4] value in 50% of the patients, divided by a factor of ~ 1.25 (within +/- 10%). The factor of 1.25 stems from the lack of postoperative use of thyroidal triiodothyronine (T3). Furthermore, approximately 25% of the patients presented a greater preoperative [FT4] difference than postoperative [FT4]/1.25 combined with a normal [TSH] difference. Based on these observations, the effect of T3 on the value of the [FT4] set point was analyzed and explained from a control theory perspective.

A recent paper shows that in gene expression space the manifold spanned by normal tissues and the manifold spanned by the corresponding tumors are disjoint. The statement is based on a two-dimensional projection of gene expression data. In the present paper, we show that, for the multi-dimensional vectors defining the centers of cloud samples: 1. The closest tumor to a given normal tissue is the tumor developed in that tissue, 2. Two normal tissues define quasi-orthogonal directions, 3. A tumor may have a projection onto its corresponding normal tissue, but it is quasi-orthogonal to all other normal tissues, and 4. The cancer manifold is roughly obtained by translating the normal tissue manifold along an orthogonal direction defined by a global cancer progression axis. These geometrical properties add a new characterization of normal tissues and tumors and may have biological significance. Indeed, normal tissues at the vertices of a high-dimensional simplex could indicate genotype optimization for given tissue functions, and a way of avoiding errors in embryonary development. On the other hand, the cancer progression axis could define relevant pan-cancer genes and seems to be consistent with the atavistic theory of tumors.

In angiosperms cytoplasmic DNA is typically passed on maternally through ovules. Genes in the mtDNA may cause male sterility. When male-sterile (female) cytotypes produce more seeds than cosexuals, they pass on more copies of their mtDNA and will co-occur with cosexuals with a neutral cytotype. Cytoplasmic gynodioecy is a well-known phenomenon in angiosperms, both in wild and crop plants. In some conifer families (e.g. Pinaceae) mitochondria are also maternally inherited. However in some other families (e.g. Taxaceae and Cupressaceae) mtDNA is paternally inherited through the pollen. With paternal mtDNA inheritance, male cytotypes that produce more pollen than cosexuals are expected to co-occur with cosexuals. This is uncharted territory. An ESS model shows that the presence of male cytotypes selects for more female allocation in the cosexual, i.e. for sexual specialisation. An allele that switches sex from male to female can then invade. This leads to rapid loss of the neutral cytotype of the cosexual, fixation of the male cytotype and dioecy with 50% males and 50% females. The models suggest that paternal inheritance of mtDNA facilitates the evolution dioecy. Consistent with this hypothesis the Pinaceae are 100% monoecious, while dioecy is common in the Taxaceae family and in the genus Juniperus (Cupressaceae). However, no reliable data are yet available on both mode of inheritance of mtDNA and gender variation of the same species. When cosexuals benefit from reproductive assurance (high selfing rate, low inbreeding depression, low fertilisation) they maintain themselves next to males and females. This predicted pattern with three sex types present in the same population is observed in conifers in nature.

Plants are capable of a range of complex interactions with the environment. Over the last decade, some authors have used this as evidence to argue that plants are cognitive agents. While there is no consensus on this view, it is certainly interesting to approach the debate from a comparative perspective, trying to understand whether different lineages of plants show different degrees of responsiveness to environmental cues, and how their responses compare with those of animals or humans. In this paper, I suggest that a potentially fruitful approach to these comparative studies is provided by automata theory. Accordingly, I shall present a possible application of this theory to plant communication. Two tentative results will emerge. First, that different lineages may exhibit different levels of complexity in response to similar stimuli. Second, that current evidence does not allow to infer great cognitive sophistication in plants.

The Y chromosome in the XY sex-determination system is often shorter than its X counterpart, a condition attributed to degeneration after Y recombination ceases. Contrary to the traditional view of continuous, gradual degeneration, our study reveals stabilization within large mating populations. In these populations, we demonstrate that both mutant and active alleles on the Y chromosome can reach equilibrium through a mutation-selection balance. However, the emergence of a new species, particularly through the founder effect, can disrupt this equilibrium. Specifically, if the male founders of a new species carry only a mutant allele for a particular Y-linked gene, this allele becomes fixed, leading to the loss of the corresponding active gene on the Y chromosome. Our findings suggest that the rate of Y-chromosome degeneration may be linked to the frequency of speciation events associated with single-male founder events.

The etiological account of teleological function is beset by several difficulties, which I propose to solve by grafting onto the etiological theory a subordinated goal-contribution clause. This approach enables us to ascribe neither too many teleofunctions nor too few; to give a unitary, one-clause analysis that works just as well for teleological functions derived from Darwinian evolution, as for those derived from human intention; and finally, to save the etiological theory from falsification, by explaining how, in spite of appearances, the theory can allow for evolutionary function loss.

The calcium signals regulate the production and secretion of many signaling molecules like inositol trisphosphate ([Formula: see text]) and adenosine triphosphate (ATP) in various cells including pancreatic [Formula: see text]-cells. The calcium signaling mechanisms regulating [Formula: see text], ATP and insulin responsible for various functions of [Formula: see text]-cells are still not well understood. Any disturbance in these mechanisms can alter the functions of [Formula: see text]-cells leading to diabetes and metabolic disorders. Therefore, a mathematical model is proposed by incorporating the reaction-diffusion equation for calcium dynamics and a system of first-order differential equations for [Formula: see text], ATP-production and insulin secretion with initial and boundary conditions. The model incorporates the temporal dependence of [Formula: see text]-production and degradation, ATP production and insulin secretion on calcium dynamics in a [Formula: see text]-cell. The piecewise linear finite element method has been used for the spatial dimension and the Crank-Nicolson scheme for the temporal dimension to obtain numerical results. The effect of changes in source influxes and buffers on calcium dynamics and production of [Formula: see text], ATP and insulin levels in a [Formula: see text]-cell has been analyzed. It is concluded that the dysfunction of source influx and buffers can cause significant variations in calcium levels and dysregulation of [Formula: see text], ATP and insulin production, which can lead to various metabolic disorders, diabetes, obesity, etc. The proposed model provides crucial information about the changes in mechanisms of calcium dynamics causing proportionate disturbances in [Formula: see text], ATP and insulin levels in pancreatic cells, which can be helpful for devising protocols for diagnosis and treatment of various metabolic diseases.

The globalization in business and tourism becomes crucial more and more for the economical sustainability of local communities. In the presence of an epidemic outbreak, there must be such a decision on the policy by the host community as whether to accept visitors or not, the number of acceptable visitors, or the condition for acceptable visitors. Making use of an SIRI type of mathematical model, we consider the influence of visitors on the spread of a reinfectious disease in a community, especially assuming that a certain proportion of accepted visitors are immune. The reinfectivity of disease here means that the immunity gained by either vaccination or recovery is imperfect. With the mathematical results obtained by our analysis on the model for such an epidemic dynamics of resident and visitor populations, we find that the acceptance of visitors could have a significant influence on the disease's endemicity in the community, either suppressive or supportive.

This paper focuses on physiological integration in multicellular systems, a notion often associated with biological individuality, but which has not received enough attention and needs a thorough theoretical treatment. Broadly speaking, physiological integration consists in how different components come together into a cohesive unit in which they are dependent on one another for their existence and activity. This paper argues that physiological integration can be understood by considering how the components of a biological multicellular system are controlled and coordinated in such a way that their activities can contribute to the maintenance of the system. The main implication of this perspective is that different ways of controlling their parts may give rise to multicellular organizations with different degrees of integration. After defining control, this paper analyses how control is realized in two examples of multicellular systems located at different ends of the spectrum of multicellularity: biofilms and animals. It focuses on differences in control ranges, and it argues that a high degree of integration implies control exerted at both medium and long ranges, and that insofar as biofilms lack long-range control (relative to their size) they can be considered as less integrated than other multicellular systems. It then discusses the implication of this account for the debate on physiological individuality and the idea that degrees of physiological integration imply degrees of individuality.

The fundamental Hennigian principle, grouping solely on synapomorphy, is seldom used in modern phylogenetics. In the submitted paper, we apply this principle in reanalyzing five datasets comprising 197 complete plastid genomes (plastomes). We focused on the latter because plastome-based DNA sequence data gained dramatic popularity in molecular systematics during the last decade. We show that pattern-cladistic analyses based on complete plastid genome sequences can successfully resolve affinities between plant taxa, simultaneously simplifying both the genomic and analytical frameworks of phylogenetic studies. We developed "Matrix to Newick" (M2N), a program to represent the standard molecular alignment of plastid genomes in the form of trees or relationships directly. Thus, massive plastome-based DNA sequence data can be successfully represented in a relational form rather than as a standard molecular alignment. Application of methods of median supertree construction (the Average Consensus method has been used as an example in this study) or Maximum Parsimony analysis to relational representations of plastome sequence data may help systematist to avoid the complicated assumption-based frameworks of Maximum Likelihood or Bayesian phylogenetics that are most used today in massive plastid sequence data analyses. We also found that significant amounts of pure genomic information that typically accommodate the majority of current plastid phylogenomic studies can be effectively dropped by systematists if they focus on the pattern-cladistics or relational analyses of plastome-based molecular data. The proposed pattern-cladistic approach is a powerful and straightforward heuristic alternative to modern plastome-based phylogenetics.

The central dogma of molecular biology dictates that, with only a few exceptions, information proceeds from DNA to protein through an RNA intermediate. Examining the enigmatic steps from prebiotic to biological chemistry, we take another road suggesting that primordial peptides acted as template for the self-assembly of the first nucleic acids polymers. Arguing in favour of a sort of archaic "reverse translation" from proteins to RNA, our basic premise is a Hadean Earth where key biomolecules such as amino acids, polypeptides, purines, pyrimidines, nucleosides and nucleotides were available under different prebiotically plausible conditions, including meteorites delivery, shallow ponds and hydrothermal vents scenarios. Supporting a protein-first scenario alternative to the RNA world hypothesis, we propose the primeval occurrence of short two-dimensional peptides termed "selective amino acid- and nucleotide-matching oligopeptides" (henceforward SANMAOs) that noncovalently bind at the same time the polymerized amino acids and the single nucleotides dispersed in the prebiotic milieu. In this theoretical paper, we describe the chemical features of this hypothetical oligopeptide, its biological plausibility and its virtues from an evolutionary perspective. We provide a theoretical example of SANMAO's selective pairing between amino acids and nucleosides, simulating a poly-Glycine peptide that acts as a template to build a purinic chain corresponding to the glycine's extant triplet codon GGG. Further, we discuss how SANMAO might have endorsed the formation of low-fidelity RNA's polymerized strains, well before the appearance of the accurate genetic material's transmission ensured by the current translation apparatus.

The aim of this paper is to investigate the role of water stress on plants production. We propose a mathematical model for the dynamics growth of plants that takes into account the concentration of available water in the soil, water stress, plant production and plants compensation. Sensitivity analysis of the model has been performed in order to determine the impact of related parameters on the dynamics growth of plants. We present the theoretical analysis of the model with and without water stress. More precisely, we show that the full model is well-posedness. For each model, we compute the trivial equilibria and derive two thresholds parameters that determine the outcome of water stress within a plantation. Further, we perform numerical simulation on the case of banana-plantain simulations to support the theory. We found that the Hopf bifurcation occurs for a specific value of the water absorption rate of unstressed plants. The impact of the water stress on the banana-plantain production is also numerically investigated. After, the role of the water stress on the plant production is numerically investigated. We found that the water stress can cause about 68.16% of loss of banana-plantain production within a plantation with 1600 rejets initially planted. This suggests that climate change plays a detrimental role on banana-plantains production.

The emergence of an autocatalytic network from an available set of elements is a fundamental step in early evolutionary processes, such as the origin of metabolism. Given the set of elements, the reactions between them (chemical or otherwise), and with various elements catalysing certain reactions, a Reflexively Autocatalytic F-generated (RAF) set is a subset R[Formula: see text] of reactions that is self-generating from a given food set, and with each reaction in R[Formula: see text] being catalysed from within R[Formula: see text]. RAF theory has been applied to various phenomena in theoretical biology, and a key feature of the approach is that it is possible to efficiently identify and classify RAFs within large systems. This is possible because RAFs can be described as the (nonempty) subsets of the reactions that are the fixed points of an (efficiently computable) interior map that operates on subsets of reactions. Although the main generic results concerning RAFs can be derived using just this property, we show that for systems with at least 12 reactions there are generic results concerning RAFs that cannot be proven using the interior operator property alone.Kindly check and confirm the edit made in the title.I confirm that the edit is fine.

Targeted hypermutation has proven to be a useful survival strategy for bacteria under severe stress and is also used by multicellular organisms in specific instances such as the mammalian immune system. This might appear surprising, given the generally observed deleterious effects of poor replication fidelity/high mutation rate. A previous theoretical model designed to explore the role of replication fidelity in the origin of life was applied to a simulated hypermutation scenario. The results confirmed that the same model is useful for analyzing hypermutation and can predict the effects of the same parameters (survival probability, replication fidelity, mutation effect, and others) on the survival of cellular populations undergoing hypermutation as a result of severe stress.

The variance effective population size ([Formula: see text]) is frequently used to quantify the expected rate at which a population's allele frequencies change over time. The purpose of this paper is to find expressions for the global [Formula: see text] of a spatially structured population that are of interest for conservation of species. Since [Formula: see text] depends on allele frequency change, we start by dividing the cause of allele frequency change into genetic drift within subpopulations (I) and a second component mainly due to migration between subpopulations (II). We investigate in detail how these two components depend on the way in which subpopulations are weighted as well as their dependence on parameters of the model such a migration rates, and local effective and census sizes. It is shown that under certain conditions the impact of II is eliminated, and [Formula: see text] of the metapopulation is maximized, when subpopulations are weighted proportionally to their long term reproductive contributions. This maximal [Formula: see text] is the sought for global effective size, since it approximates the gene diversity effective size [Formula: see text], a quantifier of the rate of loss of genetic diversity that is relevant for conservation of species and populations. We also propose two novel versions of [Formula: see text], one of which (the backward version of [Formula: see text]) is most stable, exists for most populations, and is closer to [Formula: see text] than the classical notion of [Formula: see text]. Expressions for the optimal length of the time interval for measuring genetic change are developed, that make it possible to estimate any version of [Formula: see text] with maximal accuracy.

Let the individuals of a population be divided into two groups with different personal habits. The core group is associated with health risk behaviors; the non-core group avoids unhealthy activities. Assume that the infected individuals of the core group can spread a contagious disease to the whole population. Also, assume that cure does not confer immunity. Here, an epidemiological model written as a set of ordinary differential equations is proposed to investigate the infection propagation in this population. In the model, migrations between these two groups are allowed; however, the transitions from the non-core group into the core group prevail. These migrations can be either spontaneous or stimulated by social pressure. It is analytically shown that, in the scenario of spontaneous migration, the disease is either naturally eradicated or chronically persists at a constant level. In the scenario of stimulated migration, in addition to eradication and constant persistence, self-sustained oscillations in the number of sick individuals can also be found. These analytical results are illustrated by numerical simulations and discussed from a public health perspective.