scholarly journals ATG13 dynamics in non-selective autophagy and mitophagy: insights from live imaging studies and mathematical modelling

2018 ◽  
Author(s):  
Piero Dalle Pezze ◽  
Eleftherios Karanasios ◽  
Varvara Kandia ◽  
Maria Manifava ◽  
Simon A. Walker ◽  
...  
Keyword(s):  
Experimental Data ◽  
Mathematical Model ◽  
Mathematical Modelling ◽  
Normal Distribution ◽  
Live Imaging ◽  
Oscillatory Behaviour ◽  
Imaging Studies ◽  
Selective Autophagy ◽  
Log Normal ◽  
Log Normal Distribution

AbstractDuring autophagy, the ULK complex nucleates autophagic precursors which give rise to autophagosomes. We analysed by live imaging and mathematical modelling translocation of ATG13 (part of ULK complex) to autophagic puncta in starvation-induced autophagy and ivermectin-induced mitophagy. In non-selective autophagy, the intensity and duration of ATG13 translocation approximated a normal distribution whereas wortmannin reduced this and shifted to a log-normal distribution. During mitophagy, multiple translocations of ATG13, with increasing time between peaks were observed. We hypothesised that these multiple translocations arise because engulfment of mitochondrial fragments requires successive nucleations of multiple phagophores on the same target, and a mathematical model based on this idea reproduced the oscillatory behaviour. Significantly, model and experimental data were also in agreement that the number of ATG13 translocations is directly proportional to the diameter of the targeted mitochondrial fragments. Our data provide novel insights into the early dynamics of selective and non-selective autophagy.

Modeling Dislocation Loop Nucleation and Evolution in Germanium, Arsenic and Boron Implanted Silicon

2002 ◽  
Vol 717 ◽  
Author(s):  
Ibrahim Avci ◽  
Mark E. Law
Keyword(s):  
Experimental Data ◽  
Normal Distribution ◽  
Dislocation Loop ◽  
Evolution Model ◽  
Experimental Results ◽  
Projected Range ◽  
Defect Nucleation ◽  
Log Normal ◽  
Log Normal Distribution

AbstractA loop nucleation and evolution model in Si+ implanted Silicon was previously introduced [1]. In this study, the model is extended to predict end of range (EOR) and projected range defect nucleation and evolution created by different ion implant species such as Germanium, Arsenic and Boron. The model assumes that all the nucleated loops come from {311} unfaulting and the loop density and average loop radius follow a log normal distribution. The model is verified with the experimental data obtained from literature for Germanium [2], Arsenic [3] and Boron [4] implanted Silicon for different implant doses and energies. Modeling results are in agreement with the experimental results.

scholarly journals Peculiarities of data processing for optical measurements of disperse parameters of bimodal media

2019 ◽  
Vol 43 (4) ◽  
pp. 692-698 ◽  
Author(s):  
A.A. Zhirnov ◽  
O.B. Kudrjashova
Keyword(s):  
Experimental Data ◽  
Particle Size ◽  
Distribution Function ◽  
Particulate Matter ◽  
Particle Size Distribution ◽  
Normal Distribution ◽  
Size Distribution ◽  
A Priori ◽  
Log Normal ◽  
Log Normal Distribution

This study is focused on enhancing the informativity of optical measurement techniques for particulate matter. The problem is that the description of particulate matter with bimodal and multimodal distributions by an a priori defined analytical function of particle size distribution (for example, a log-normal distribution) is not accurate enough. Here, we explore if experimental data can be approximated by a multivariable function of particle size distribution instead of using the a priori defined log-normal distribution. For the comparison of the approximation results, experiments are conducted on standard samples with granulometric compositions OGS-01LM and OGS-08LM separately and jointly in a mix. The experimental data are recorded by a high-selectivity turbidimetric technique in water suspensions of these samples. The purpose of this study is to present the measurement results as a distribution function that enables one to identify more accurately the particle-size distribution profile and the corresponding disperse characteristics of the aerosol in question when measuring parameters of disperse media by optical techniques. The main objective of this work is to develop, implement and verify a search algorithm for the particle-size distribution function by way of a multi-parameter function. We show that the solution to the problem proposed herein is more universal because it allows slow and fast processes in suspensions and aerosols to be examined with a lower error. The algorithm can be applied to the problems which are based on solving first-kind Fredholm equations.

scholarly journals A Universal Model for the Log-Normal Distribution of Elasticity in Polymeric Gels and Its Relevance to Mechanical Signature of Biological Tissues

Biology ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 64
Author(s):  
Arnaud Millet
Keyword(s):  
Elastic Modulus ◽  
Normal Distribution ◽  
Biological Tissues ◽  
Force Microscopy ◽  
Polymeric Gels ◽  
Atomic Force ◽  
Clear Explanation ◽  
Log Normal ◽  
Log Normal Distribution

The mechanosensitivity of cells has recently been identified as a process that could greatly influence a cell’s fate. To understand the interaction between cells and their surrounding extracellular matrix, the characterization of the mechanical properties of natural polymeric gels is needed. Atomic force microscopy (AFM) is one of the leading tools used to characterize mechanically biological tissues. It appears that the elasticity (elastic modulus) values obtained by AFM presents a log-normal distribution. Despite its ubiquity, the log-normal distribution concerning the elastic modulus of biological tissues does not have a clear explanation. In this paper, we propose a physical mechanism based on the weak universality of critical exponents in the percolation process leading to gelation. Following this, we discuss the relevance of this model for mechanical signatures of biological tissues.

Sign in / Sign up

Export Citation Format

Share Document