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“In Part I of this work, we carried out a logical analysis of a simple model describing the interplay between protein p53, its main negative regulator Mdm2 and DNA damage, and briefly discussed the corresponding differential model (Abou-Jaoude et al, 2009). This analysis allowed us to reproduce several qualitative features of the kinetics of the p53 response to damage and provided an interpretation of the short and long characteristic periods of oscillation reported by Geva-Zatorsky et al. (2006) depending on the irradiation dose Starting from this analysis, we focus here on more quantitative aspects of Talazoparib datasheet the dynamics of our network and combine the differential description of our system with stochastic

simulations which take molecular fluctuations into account We find that the amplitude of the p53 and Mdm2 oscillations is highly variable (to a degree that depends, however, on the bifurcation properties of the system) In contrast, peak width and timing remain more regular, consistent with the experimental data Our simulations also show that noise can induce repeated pulses

of p53 and Mdm2 that, at low damage, resemble the slow irregular fluctuations observed experimentally. EPZ004777 in vivo Adding the stochastic dimension in our modeling further allowed us to account for an increase of the fraction of cells oscillating with a high frequency when the irradiation dose increases, as observed by Geva-Zatorsky et al. (2006) (C) 2010 Elsevier Ltd. All rights reserved”
“Electroencephalographic slow-wave activity (EEG SWA) is an electrophysiological signature of slow (0.5 to 4.0 Hz), synchronized, oscillatory neocortical activity. In healthy individuals, EEG SWA is Galactokinase maximally expressed during non-rapid-eye-movement (non-REM) sleep, and intensifies as a function of prior wake duration.

Many of the cellular and network mechanisms generating EEG SWA have been identified, but a number of questions remain unanswered. For example, although EEG SWA is a marker of sleep need, its precise relationship with sleep homeostasis and its roles in the brain are unknown. In this review, the authors discuss their current understanding of the neural mechanisms and possible functions of EEG SWA.”
“Infection elimination may be an important goal of control programs Only in stochastic infection models can true infection elimination be observed as a fadeout. The phenomena of fadeout and variable prevalence are important in understanding the transmission dynamics of infectious diseases and these phenomena are essential to evaluate the effectiveness of control measures To investigate the stochastic dynamics of Mycobacterium avium subsp paratuberculosis (MAP) infection on US dairy herds with test-based culling intervention, we developed a multi-group stochastic compartmental model (a continuous time Markov chain model) with both horizontal and vertical transmission.