Stochastic timing in gene expression for simple regulatory strategies

Timing is essential for many cellular processes, from cellular responses to external stimuli to the cell cycle and circadian clocks. Many of these processes are based on gene expression. For example, an activated gene may be required to reach in a precise time a threshold level of expression that triggers a specific downstream process. However, gene expression is subject to stochastic fluctuations, naturally inducing an uncertainty in this threshold-crossing time with potential consequences on biological functions and phenotypes. Here, we consider such "timing fluctuations", and we ask how they can be controlled. Our analytical estimates and simulations show that, for an induced gene, timing variability is minimal if the threshold level of expression is approximately half of the steady-state level. Timing fuctuations can be reduced by increasing the transcription rate, while they are insensitive to the translation rate. In presence of self-regulatory strategies, we show that self-repression reduces timing noise for threshold levels that have to be reached quickly, while selfactivation is optimal at long times. These results lay a framework for understanding stochasticity of endogenous systems such as the cell cycle, as well as for the design of synthetic trigger circuits.Comment: 10 pages, 5 figure

Promoting human rights and achieving reconciliation at the international level (part 2)

No Abstrac

Promoting human rights and achieving reconciliation at the international level (part 1)

No Abstrac

Global dynamics of microbial communities emerge from local interaction rules

Most microbes live in spatially structured communities (e.g., biofilms) in which they interact with their neighbors through the local exchange of diffusible molecules. To understand the functioning of these communities, it is essential to uncover how these local interactions shape community-level properties, such as the community composition, spatial arrangement, and growth rate. Here, we present a mathematical framework to derive community-level properties from the molecular mechanisms underlying the cell-cell interactions for systems consisting of two cell types. Our framework consists of two parts: a biophysical model to derive the local interaction rules (i.e. interaction range and strength) from the molecular parameters underlying the cell-cell interactions and a graph based model to derive the equilibrium properties of the community (i.e. composition, spatial arrangement, and growth rate) from these local interaction rules. Our framework shows that key molecular parameters underlying the cell-cell interactions (e.g., the uptake and leakage rates of molecules) determine community-level properties. We apply our model to mutualistic cross-feeding communities and show that spatial structure can be detrimental for these communities. Moreover, our model can qualitatively recapitulate the properties of an experimental microbial community. Our framework can be extended to a variety of systems of two interacting cell types, within and beyond the microbial world, and contributes to our understanding of how community-level properties emerge from microscopic interactions between cells

Effects of state dependent correlations on nucleon density and momentum distributions

The proton momentum and density distributions of closed shell nuclei are calculated within a model treating short--range correlations up to first order in the cluster expansion. The validity of the model is verified by comparing the results obtained with purely scalar correlations with those produced by finite nuclei Fermi Hypernetted Chain calculations. State dependent correlations are used to calculate momentum and density distributions of 12C, 16O, 40Ca, and 48Ca, and the effects of their tensor components are studied.Comment: 16 pages, latex, 8 figures, accepted for publication in Phys. Rev.

Short-range correlations and meson exchange currents in photonucleon emission

One-nucleon emission processes induced by photon absorption are studied by considering short-range correlations effects. At energies above the giant resonance region the validity of the direct knock-out model has been tested by comparison with continuum Random Phase Approximation results. Nucleon re-scattering effects have been considered by using an optical potential. The role of the electromagnetic convection, magnetization and meson exchange currents has been investigated as a function of both excitation energy and momentum transfer. The short-range correlation effects have been studied by using various correlation functions. We found that the nucleon photo-emission cross section is rather sensitive to the presence of short-range correlations at large values of nucleon emission angle. In this region, however, the effects of meson exchange currents are even larger than those produced by short-range correlations.Comment: 37 pages, 20 figures in postscript, Text in LaTe

Stochastic timing in gene expression for simple regulatory strategies

Timing is essential for many cellular processes, from cellular responses to external stimuli to the cell cycle and circadian clocks. Many of these processes are based on gene expression. For example, an activated gene may be required to reach in a precise time a threshold level of expression that triggers a specific downstream process. However, gene expression is subject to stochastic fluctuations, naturally inducing an uncertainty in this threshold-crossing time with potential consequences on biological functions and phenotypes. Here, we consider such \u2018timing fluctuations\u2019 and we ask how they can be controlled. Our analytical estimates and simulations show that, for an induced gene, timing variability is minimal if the threshold level of expression is approximately half of the steady-state level. Timing fluctuations can be reduced by increasing the transcription rate, while they are insensitive to the translation rate. In presence of self-regulatory strategies, we show that self-repression reduces timing noise for threshold levels that have to be reached quickly, while self-activation is optimal at long times. These results lay a framework for understanding stochasticity of endogenous systems such as the cell cycle, as well as for the design of synthetic trigger circuits

Phase field approach to optimal packing problems and related Cheeger clusters

In a fixed domain of $\Bbb{R}^N$ we study the asymptotic behaviour of optimal clusters associated to $\alpha$-Cheeger constants and natural energies like the sum or maximum: we prove that, as the parameter $\alpha$ converges to the "critical" value $\Big (\frac{N-1}{N}\Big ) _+$, optimal Cheeger clusters converge to solutions of different packing problems for balls, depending on the energy under consideration. As well, we propose an efficient phase field approach based on a multiphase Gamma convergence result of Modica-Mortola type, in order to compute $\alpha$-Cheeger constants, optimal clusters and, as a consequence of the asymptotic result, optimal packings. Numerical experiments are carried over in two and three space dimensions

Antisymmetrized Green's function approach to (e,e′)(e,e') reactions with a realistic nuclear density

A completely antisymmetrized Green's function approach to the inclusive quasielastic $(e,e')$ scattering, including a realistic one-body density, is presented. The single particle Green's function is expanded in terms of the eigenfunctions of the nonhermitian optical potential. This allows one to treat final state interactions consistently in the inclusive and in the exclusive reactions. Nuclear correlations are included in the one-body density. Numerical results for the response functions of $^{16}$O and $^{40}$Ca are presented and discussed.Comment: 45 pages, 3 figure