MODELLING THE ROLE OF IMMUNITY IN MACROPARASITE INFECTIONS

Abstract The CII protein of temperate coliphage 186, like the unrelated CII protein of phage λ, is a transcriptional activator that primes expression of the CI immunity repressor and is critical for efficient establishment of lysogeny. 186-CII is also highly unstable, and we show that in vivo degradation is mediated by both FtsH and RseP. We investigated the role of CII instability by constructing a 186 phage encoding a protease resistant CII. The stabilised-CII phage was defective in the lysis-lysogeny decision: choosing lysogeny with close to 100% frequency after infection, and forming prophages that were defective in entering lytic development after UV treatment. While lysogenic CI concentration was unaffected by CII stabilisation, lysogenic transcription and CI expression was elevated after UV. A stochastic model of the 186 network after infection indicated that an unstable CII allowed a rapid increase in CI expression without a large overshoot of the lysogenic level, suggesting that instability enables a decisive commitment to lysogeny with a rapid attainment of sensitivity to prophage induction.

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Deterministic and Stochastic Model for the Role of the Immune Response Time Delay in Periodic Therapy of the Tumors

Current Computer - Aided Drug Design ◽

10.2174/157340911798260313 ◽

2011 ◽

Vol 7 (4) ◽

pp. 338-350 ◽

Cited By ~ 2

Author(s):

Oana Chis ◽

Mihaela Neamtu ◽

Dumitru Opris

Keyword(s):

Immune Response ◽

Time Delay ◽

Stochastic Model ◽

Response Time

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The photo-orientation of azobenzene in viscous solutions, simulated by a stochastic model

Physical Chemistry Chemical Physics ◽

10.1039/c4cp03472d ◽

2014 ◽

Vol 16 (45) ◽

pp. 25081-25092 ◽

Cited By ~ 5

Author(s):

Valentina Cantatore ◽

Giovanni Granucci ◽

Maurizio Persico

Keyword(s):

Stochastic Model ◽

Nonadiabatic Dynamics ◽

Viscous Solutions

Simulations of the photo-orientation of azobenzene in a viscous solvent, based on nonadiabatic dynamics results, highlight the role of photoisomerization.

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Textural Variations in B-Mode Ultrasonography: A Stochastic Model

Ultrasonic Imaging ◽

10.1177/016173468100300302 ◽

1981 ◽

Vol 3 (3) ◽

pp. 235-257 ◽

Cited By ~ 33

Author(s):

Stephen W. Flax ◽

Gary H. Glover ◽

Norbert J. Pelc

Keyword(s):

Stochastic Model ◽

Clinical Diagnosis ◽

Spatial Resolution ◽

Imaging System ◽

Experimental Results ◽

Texture Formation ◽

Tissue Microstructure ◽

Analytic Models ◽

Insight Into

Analysis of textural patterns in gray-scale ultrasonography is frequently the basis for clinical diagnosis. It has been found, however, that texture is shaped not only by tissue microstructure but by characteristics of the imaging system as well. This paper describes computer and analytic models which give insight into the role of the imager in texture formation. It is shown that spatial resolution and texture granularity are not simply related, and that axial and lateral texture are determined by unrelated phenomena. Experimental results are given which confirm the modeling.

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Role of competition in the strain structure of rotavirus under invasion and reassortment

10.1101/137661 ◽

2017 ◽

Cited By ~ 1

Author(s):

Daniel Zinder ◽

Maria A Riolo ◽

Robert J. Woods ◽

Mercedes Pascual

Keyword(s):

Stochastic Model ◽

Sequence Data ◽

Strain Theory ◽

Competitive Interactions ◽

Viral Pathogens ◽

Present Evidence ◽

Frequency Dependent Selection ◽

Common Cause ◽

Cross Immunity

ABSTRACTThe role of competitive interactions in the formation and coexistence of viral strains remains unresolved. Neglected aspects of existing strain theory are that viral pathogens are repeatedly introduced from animal sources and readily exchange their genes. The combined effect of introduction and reassortment opposes strain structure, in particular the predicted stable coexistence of antigenically differentiated strains under strong frequency-dependent selection mediated by cross-immunity. Here we use a stochastic model motivated by rotavirus, the most common cause of childhood diarrheal mortality, to investigate serotype structure under these conditions. We describe a regime in which the transient coexistence of distinct strains emerges despite only weak cross-immunity, but is disturbed by invasions of new antigenic segments that reassort into existing backgrounds. We find support for this behavior in global rotavirus sequence data and present evidence for the displacement of new strains towards open antigenic niches. Our work extends previous work to bacterial and viral pathogens that share these rotavirus-like characteristics, with important implications for the effects of interventions such as vaccination on strain composition, and for the understanding of the factors promoting emergence of new subtypes.

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Bursting on a two state stochastic model for gene transcription in Drosophila embryos

10.1101/107979 ◽

2017 ◽

Author(s):

Romain Yvinec ◽

Luiz Guilherme S. da Silva ◽

Guilherme N. Prata ◽

John Reinitz ◽

Alexandre Ferreira Ramos

Keyword(s):

Experimental Data ◽

Stochastic Model ◽

Gene Transcription ◽

Fruit Fly ◽

Synthesis Rate ◽

Recent Experimental Data ◽

Gillespie Algorithm ◽

Noisy Environment ◽

Intrinsic Stochasticity

AbstractRecent experimental data on the transcription dynamics of eve gene stripe two formation of Drosophila melanogaster embryos occurs in bursts of multiple sizes and durations. That has motivated the proposition of a transcription model having multiple ON states for the promoter of the eve gene each of them characterized by different synthesis rate. To understand the role of multiple ON states on gene transcription we approach the exact solutions for a two state stochastic model for gene transcription in D. melanogaster embryos and derive its bursting limit. Simulations based on the Gillespie algorithm at the bursting limit show the occurrence of bursts of multiple sizes and durations. Based on our theoretical approach, we interpret the aforementioned experimental data as a demonstration of the intrinsic stochasticity of the transcriptional processes in fruit fly embryos. Then, we conceive the experimental arrangement to determine when gene transcription has multiple ON promoter state in a noisy environment.

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Modeling disease spread in populations with birth, death, and concurrency

10.1101/087213 ◽

2016 ◽

Author(s):

Joel C. Miller ◽

Anja C. Slim

Keyword(s):

Stochastic Model ◽

Large Population ◽

Dynamic Network ◽

Disease Spread ◽

Initial Growth ◽

Concurrent Partnerships ◽

Equilibrium Size ◽

The Impact ◽

Concurrent Relationships

AbstractThe existence of sexual partnerships that overlap in time (concurrent relationships) is believed by some to be a significant contributing factor to the spread of HIV, although this is controversial. We derive an analytic model which allows us to investigate and compare disease spread in populations with and without concurrency. We can identify regions of parameter space in which its impact is negligible, and other regions in which it plays a major role. We also see that the impact of concurrency on the initial growth phase can be much larger than its impact on the equilibrium size. We see that the effect of concurrency saturates, which leads to the perhaps surprising conclusion that interventions targeting concurrency may be most effective in populations with low to moderate levels of concurrency.Author SummaryWe consider the spread of an infectious disease through a population modeled by a dynamic network with demographic turnover. We develop a stochastic model of the disease and derive governing equations that exactly predict the large population (deterministic) limit of the stochastic model. We use this to investigate the role of concurrency and find that interventions targeting concurrency may be most effective in populations with lower levels of concurrency.Our model is not intended to be an accurate representation of any single population. Rather it is intended to give general insights for intervention design and to provide a framework which can be further specialized to particular populations.This model is the first model to allow for analytic investigation of the impact of concurrent partnerships in a population exhibiting demographic turnover. Thus it will be useful for investigating the “concurrency hypothesis.”

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