Living cells sense noisy biochemical signals crucial for survival, yet models incorporating intracellular signaling are limited. This study examines how cells sense chemotactic concentrations through phosphorylation readouts in Ca2+ signaling, which is ubiquitous in most eukaryotic cells. Using stochastic simulations and analytical calculations we find that concentration sensing remains robust to variations in cytoplasmic reaction rates once they exceed a certain value, suggesting a potential evolutionary advantage that allows cells to optimize other signaling tasks without compromising concentration sensing accuracy. Our analysis demonstrates theoretically that Dictyostelium is capable of sensing very low concentrations of cyclic adenosine monophosphate (cAMP) as is experimentally seen.
Hope Renfroe-Becton, Kendall R. Kirk, Daniel J. Anco
Peanut foliar diseases and disorders can be difficult to rapidly diagnose with little experience because some abiotic and biotic symptoms present similar symptoms. Developing algorithms for automated identification of peanut foliar diseases and disorders could potentially provide a quick, affordable, and easy method for diagnosing peanut symptoms. To examine this, images of peanut leaves were captured from various angles, distances, and lighting conditions using various cameras. Color space data from all images was subsequently extracted and subjected to logistic regression. Separate algorithms were developed for each symptom to include healthy, hopperburn, late leaf spot, Provost injury, tomato spotted wilt, paraquat injury, or surfactant injury. The majority of these symptoms are not included within currently available disease identification mobile apps. All of the algorithms developed for peanut foliar diagnostics were ≥ 86% accurate. These diagnostic algorithms have the potential to be a valuable tool for growers if made available via a web-accessible platform, which is the next step of this work.
One of the causes of high fidelity of copying in biological systems is kinetic discrimination. In this mechanism larger dissipation and copying velocity result in improved copying accuracy. We consider a model of a polymerase which simultaneously copies a single stranded RNA and opens a single- to double-stranded junction serving as an obstacle. The presence of the obstacle slows down the motor, resulting in a change of its fidelity, which can be used to gain information about the motor and junction dynamics. We find that the motor's fidelity does not depend on details of the motor-junction interaction, such as whether the interaction is passive or active. Analysis of the copying fidelity can still be used as a tool for investigating the junction kinetics.
We study the coarsening of strongly microphase separated membrane domains in the presence of recycling of material. We study the dynamics of the domain size distribution under both scale-free and size-dependent recycling. Closed form solutions to the steady state distributions and its associated central moments are obtained in both cases. Moreover, for the size-independent case, the~time evolution of the moments is analytically calculated, which provide us with exact results for their corresponding relaxation times. Since these moments and relaxation times are measurable quantities, the biophysically significant free parameters in our model may be determined by comparison with experimental data.
A certain class of viruses replicates inside a cell if they can enter the nucleus through one of many small target pores, before being permanently trapped or degraded. We adopt for viral motion a switching stochastic process model and we estimate here the probability and the conditional mean first passage time for a viral particle to attain alive the nucleus. The cell nucleus is covered with thousands of small absorbing nuclear pores and the minimum distance between them defines the smallest spatial scale that limits the efficiency of stochastic simulations. Using the Neuman-Green's function method to solve the steady-state Fokker-Planck equation, we derive asymptotic formula for the probability and mean arrival time to a small window for various pores' distributions, that agree with stochastic simulations. These formulas reveal how key geometrical parameters defines the cytoplasmic stage of viral infection.
The process of protein search for specific binding sites on DNA is fundamentally important since it marks the beginning of all major biological processes. We present a theoretical investigation that probes the role of DNA sequence symmetry, heterogeneity and chemical composition in the protein search dynamics. Using a discrete-state stochastic approach with a first-passage events analysis, which takes into account the most relevant physical-chemical processes, a full analytical description of the search dynamics is obtained. It is found that, contrary to existing views, the protein search is generally faster on DNA with more heterogeneous sequences. In addition, the search dynamics might be affected by the chemical composition near the target site. The physical origins of these phenomena are discussed. Our results suggest that biological processes might be effectively regulated by modifying chemical composition, symmetry and heterogeneity of a genome.
Recovering a stochastic process from noisy ensembles of single particle trajectories (SPTs) is resolved here using the Langevin equation as a model. The massive redundancy contained in SPTs data allows recovering local parameters of the underlying physical model. We use several parametric and non-parametric estimators to compute the first and second moment of the process and to recover the local drift, its derivative and the diffusion tensor. Using a local asymptotic expansion of the estimators and computing the empirical transition probability function, we develop here a method to deconvolve the instrumental from the physical noise. We use numerical simulations to explore the range of validity for the estimators. The present analysis allows characterizing what can exactly be recovered from the statistics of super-resolution microscopy trajectories used in molecular trafficking and underlying cellular function.
Abstract Caputo q-fractional derivatives are introduced and studied. A Caputo -type q-fractional initial value problem is solved and its solution is expressed by means of a new introduced q-Mittag–Leffler function. Some open problems about q-fractional integrals are proposed as well.
To assess Q fever in France, we analyzed data for 1985–2009 from the French National Reference Center. A total of 179,794 serum samples were analyzed; 3,723 patients (one third female patients) had acute Q fever. Yearly distribution of acute Q fever showed a continuous increase. Periodic variations were observed in monthly distribution during January 2000–December 2009; cases peaked during April–September. Q fever was diagnosed more often in patients in southeastern France, where our laboratory is situated, than in other areas. Reevaluation of the current positive predictive value of serologic analysis for endocarditis was performed. We propose a change in the phase I (virulent bacteria) immunoglobulin G cutoff titer to >1,600. Annual incidences of acute Q fever and endocarditis were 2.5/100,000 persons and 0.1/100,000 persons, respectively. Cases and outbreaks of Q fever have increased in France.
In this paper, we give relations involving values of q-Bernoulli, q-Euler, and Bernstein polynomials. Using these relations, we obtain some interesting identities on the q-Bernoulli, q-Euler, and Bernstein polynomials.