scholarly journals Mathematical Modeling and Analysis of Mitochondrial Retrograde Signaling Dynamics

2021 ◽  
Author(s):  
Shao-Ting Chiu ◽  
Wen-Wei Tseng ◽  
An-Chi Wei
Keyword(s):  
Mathematical Modeling ◽  
Retrograde Signaling ◽  
Modeling And Analysis ◽  
Signaling Dynamics ◽  
Mitochondrial Retrograde Signaling

scholarly journals Mathematical Model for the Study of Mitochondrial Retrograde Signaling Dynamics

2021 ◽  
Author(s):  
Shao-Ting Chiu ◽  
Wen-Wei Tseng ◽  
An-Chi Wei
Keyword(s):  
Mathematical Model ◽  
Quality Control ◽  
Signal Propagation ◽  
Boolean Model ◽  
Retrograde Signaling ◽  
Specific Gene ◽  
Signaling Dynamics ◽  
Model Response ◽  
Mitochondrial Retrograde Signaling ◽  
Model Dynamics

SummaryMitochondria are semi-autonomous eukaryotic organelles, that participate in energy production and metabolism, making mitochondrial quality control crucial. As most mitochondrial proteins are encoded by nuclear genes, quality control depends on proper mitochondria-nucleus communication, designated mitochondrial retrograde signaling. Early studies focused on retrograde signaling participants and specific gene knockouts. However, mitochondrial signal modulation remains elusive. Using yeast, we simulated signal propagation following mitochondrial damage and proposed a mathematical model based on enzyme kinetics and ordinary differential equations. Mitochondrial retrograde signaling decisions were described by a Boolean model. Dynamics were analyzed through an ordinary differential equation-based model and extended to evaluate the model response to noisy damage signals. Simulation revealed localized protein concentration dynamics, including waveforms, frequency response, and robustness under noise. Retrograde signaling is bistable with three localized steady states, while increased damage compromises robustness. We elucidated mitochondrial retrograde signaling, providing a basis for drug design against yeast and fungi.

The biochemistry and cell biology of aging: metabolic regulation through mitochondrial signaling

2014 ◽  
Vol 306 (6) ◽  
pp. E581-E591 ◽  
Author(s):  
Yun Chau Long ◽  
Theresa May Chin Tan ◽  
Inoue Takao ◽  
Bor Luen Tang
Keyword(s):  
Cell Biology ◽  
Metabolic Regulation ◽  
Nutrient Sensing ◽  
Cellular Aging ◽  
Retrograde Signaling ◽  
Unfolded Protein ◽  
Mitochondrial Retrograde Signaling ◽  
Long Time ◽  
Biology Of Aging ◽  
Protein Response

Cellular and organ metabolism affects organismal lifespan. Aging is characterized by increased risks for metabolic disorders, with age-associated degenerative diseases exhibiting varying degrees of mitochondrial dysfunction. The traditional view of the role of mitochondria generated reactive oxygen species (ROS) in cellular aging, assumed to be causative and simply detrimental for a long time now, is in need of reassessment. While there is little doubt that high levels of ROS are detrimental, mounting evidence points toward a lifespan extension effect exerted by mild to moderate ROS elevation. Dietary caloric restriction, inhibition of insulin-like growth factor-I signaling, and inhibition of the nutrient-sensing mechanistic target of rapamycin are robust longevity-promoting interventions. All of these appear to elicit mitochondrial retrograde signaling processes (defined as signaling from the mitochondria to the rest of the cell, for example, the mitochondrial unfolded protein response, or UPRmt). The effects of mitochondrial retrograde signaling may even spread to other cells/tissues in a noncell autonomous manner by yet unidentified signaling mediators. Multiple recent publications support the notion that an evolutionarily conserved, mitochondria-initiated signaling is central to the genetic and epigenetic regulation of cellular aging and organismal lifespan.

A Stochastic Hierarchical Population System: Excitement, Extinction and Transition to Chaos

2021 ◽  
Vol 31 (14) ◽  
Author(s):  
Irina Bashkirtseva ◽  
Tatyana Perevalova ◽  
Lev Ryashko
Keyword(s):  
Mathematical Modeling ◽  
Food Chain ◽  
Analytical Method ◽  
Three Dimensional ◽  
Biological Parameters ◽  
Top Predator ◽  
Population System ◽  
Modeling And Analysis ◽  
Transition To Chaos ◽  
Random Fluctuations

A problem of the mathematical modeling and analysis of noise-induced transformations of complex oscillatory regimes in hierarchical population systems is considered. As a key example, we use a three-dimensional food chain dynamical model of the interacting prey, predator, and top predator. We perform a comparative study of the impacts of random fluctuations on three key biological parameters of prey growth, predator mortality, and the top predator growth. A detailed investigation of the stochastic excitement, noise-induced transition from order to chaos, and various scenarios of extinction is carried out. Constructive abilities of the semi-analytical method of confidence domains in the analysis of the noise-induced extinction are demonstrated.

Mathematical Modeling and Analysis of Covid-19 Infection spreads in India with Restricted Optimal Treatment on Disease Incidence

BIOMATH ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 2106147
Author(s):  
Debkumar Pal ◽  
D Ghosh ◽  
P K Santra ◽  
G S Mahapatra
Keyword(s):  
Mathematical Modeling ◽  
Objective Function ◽  
Reproduction Number ◽  
Disease Incidence ◽  
Treatment Control ◽  
Modeling And Analysis ◽  
Proposed Model ◽  
The Cost ◽  
Disease Free ◽  
The Basic Reproduction Number

This paper presents the current situation and how to minimize its effect in India through a mathematical model of infectious Coronavirus disease (COVID-19). This model consists of six compartments to population classes consisting of susceptible, exposed, home quarantined, government quarantined, infected individuals in treatment, and recovered class. The basic reproduction number is calculated, and the stabilities of the proposed model at the disease-free equilibrium and endemic equilibrium are observed. The next crucial treatment control of the Covid-19 epidemic model is presented in India's situation. An objective function is considered by incorporating the optimal infected individuals and the cost of necessary treatment. Finally, optimal control is achieved that minimizes our anticipated objective function. Numerical observations are presented utilizing MATLAB software to demonstrate the consistency of present-day representation from a realistic standpoint.

Sign in / Sign up

Export Citation Format

Share Document