scholarly journals A game-theoretic approach to deciphering the dynamics of amyloid- β aggregation along competing pathways

2020 ◽  
Vol 7 (4) ◽  
pp. 191814 ◽  
Author(s):  
Preetam Ghosh ◽  
Pratip Rana ◽  
Vijayaraghavan Rangachari ◽  
Jhinuk Saha ◽  
Edward Steen ◽  
...  

Aggregation of amyloid- β (A β ) peptides is a significant event that underpins Alzheimer's disease (AD). A β aggregates, especially the low-molecular weight oligomers, are the primary toxic agents in AD pathogenesis. Therefore, there is increasing interest in understanding their formation and behaviour. In this paper, we use our previously established results on heterotypic interactions between A β and fatty acids (FAs) to investigate off-pathway aggregation under the control of FA concentrations to develop a mathematical framework that captures the mechanism. Our framework to define and simulate the competing on- and off-pathways of A β aggregation is based on the principles of game theory. Together with detailed simulations and biophysical experiments, our models describe the dynamics involved in the mechanisms of A β aggregation in the presence of FAs to adopt multiple pathways. Specifically, our reduced-order computations indicate that the emergence of off- or on-pathway aggregates are tightly controlled by a narrow set of rate constants, and one could alter such parameters to populate a particular oligomeric species. These models agree with the detailed simulations and experimental data on using FA as a heterotypic partner to modulate the temporal parameters. Predicting spatio-temporal landscape along competing pathways for a given heterotypic partner such as lipids is a first step towards simulating scenarios in which the generation of specific ‘conformer strains’ of A β could be predicted. This approach could be significant in deciphering the mechanisms of amyloid aggregation and strain generation, which are ubiquitously observed in many neurodegenerative diseases.

2019 ◽  
Author(s):  
Preetam Ghosh ◽  
Pratip Rana ◽  
Vijayaraghavan Rangachari ◽  
Jhinuk Saha ◽  
Edward Steen ◽  
...  

AbstractAggregation of amyloidβ(Aβ) peptides is a significant event that underpins Alzheimer disease (AD). Aβaggregates, especially the low-molecular weight oligomers, are the primary toxic agents in AD pathogenesis. Therefore, there is increasing interest in understanding their formation and behavior. In this paper, we use our previously established investigations on heterotypic interactions between Aβand fatty acids (FAs) that adopt off-fibril formation pathway under the control ofFAconcentrations, to develop a mathematical framework in defining this complex mechanism. We bring forth the use of novel game theoretic framework based on the principles of Nash equilibria to define and simulate the competing on- and off-pathways of Aβaggregation. Together with detailed simulations and biophysical experiments, our mathematical models define the dynamics involved in the mechanisms of Aβaggregation in the presence ofFAs to adopt multiple pathways. Specifically, our game theoretic model indicates that the emergence of off- or on-pathway aggregates are tightly controlled by a narrow set of rate constant parameters, and one could alter such parameters to populate a particular oligomeric species. These models agree with the detailed simulations and experimental data on usingFAas a heterotypic partner to modulate temporal parameters. Predicting spatiotemporal landscape along competing pathways for a given heterotypic partner such as biological lipids is a first step towards simulating physiological scenarios in which the generation of specific conformeric strains of Aβcould be predicted. Such an approach could be profoundly significant in deciphering the biophysics of amyloid aggregation and oligomer generation, which is ubiquitously observed in many neurodegenerative diseases.


1982 ◽  
Vol 55 (3) ◽  
pp. 367 ◽  
Author(s):  
Carl Alan Batlin ◽  
Susan Hinko

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Maya Diamant ◽  
Shoham Baruch ◽  
Eias Kassem ◽  
Khitam Muhsen ◽  
Dov Samet ◽  
...  

AbstractThe overuse of antibiotics is exacerbating the antibiotic resistance crisis. Since this problem is a classic common-goods dilemma, it naturally lends itself to a game-theoretic analysis. Hence, we designed a model wherein physicians weigh whether antibiotics should be prescribed, given that antibiotic usage depletes its future effectiveness. The physicians’ decisions rely on the probability of a bacterial infection before definitive laboratory results are available. We show that the physicians’ equilibrium decision rule of antibiotic prescription is not socially optimal. However, we prove that discretizing the information provided to physicians can mitigate the gap between their equilibrium decisions and the social optimum of antibiotic prescription. Despite this problem’s complexity, the effectiveness of the discretization solely depends on the type of information available to the physician to determine the nature of infection. This is demonstrated on theoretic distributions and a clinical dataset. Our results provide a game-theory based guide for optimal output of current and future decision support systems of antibiotic prescription.


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