Cell Survival Computation via the Generalized Stochastic Microdosimetric Model (GSM2); Part I: The Theoretical Framework

2021 ◽  
Author(s):  
Francesco G. Cordoni ◽  
Marta Missiaggia ◽  
Emanuele Scifoni ◽  
Chiara La Tessa
Keyword(s):  
Cell Survival ◽  
Linear Trend ◽  
Survival Curve ◽  
Radiation Energy ◽  
Survival Models ◽  
Linear Quadratic ◽  
Survival Fraction ◽  
Dna Damages ◽  
A Cell ◽  
High Doses

The current article presents the first application of the Generalized Stochastic Microdosimetric Model (GSM2) for computing explicitly a cell survival curve. GSM2 is a general probabilistic model that predicts the kinetic evolution of DNA damages taking full advantage of a microdosimetric description of a radiation energy deposition. We show that, despite the high generality and flexibility of GSM2, an explicit form for the survival fraction curve predicted by the GSM2 is achievable. We illustrate how several correction terms typically added a posteriori in existing radiobiological models to improve the prediction accuracy, are naturally included into GSM2. Among the most relevant features of the survival curve derived from GSM2 and presented in this article, is the linear-quadratic behavior at low doses and a purely linear trend for high doses. The study also identifies and discusses the connections between GSM2 and existing cell survival models, such as the Microdosimetric Kinetic Model (MKM) and the Multi-hit model. Several approximations to predict cell survival in different irradiation regimes are also introduced to include intercellular non-Poissonian behaviors.

scholarly journals Modelling Dose Effects from Space Irradiations: Combination of High-LET and Low-LET Radiations with a Modified Microdosimetric Kinetic Model

Life ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 161 ◽  
Author(s):  
Alejandro Bertolet ◽  
Alejandro Carabe
Keyword(s):  
Kinetic Model ◽  
Poisson Distribution ◽  
Survival Curve ◽  
X Rays ◽  
Linear Quadratic ◽  
Survival Curves ◽  
Survival Fraction ◽  
High Let ◽  
Combined Action ◽  
High Linear Energy Transfer

The Microdosimetric Kinetic Model (MKM) to predict the effects of ionizing radiation on cell colonies is studied and reformulated for the case of high-linear energy transfer (LET) radiations with a low dose. When the number of radiation events happening in a subnuclear domain follows a Poisson distribution, the MKM predicts a linear-quadratic (LQ) survival curve. We show that when few events occur, as for high-LET radiations at doses lower than the mean specific energy imparted to the nucleus, zF,n, a Poisson distribution can no longer be assumed and an initial pure linear relationship between dose and survival fraction should be observed. Predictions of survival curves for combinations of high-LET and low-LET radiations are produced under two assumptions for their comparison: independent and combined action. Survival curves from previously published articles of V79 cell colonies exposed to X-rays, α particles, Ar-ions, Fe-ions, Ne-ions and mixtures of X-rays and each one of the ions are predicted according to the modified MKM. We conclude that mixtures of high-LET and low-LET radiations may enhance the effect of individual actions due to the increase of events in domains provided by the low-LET radiation. This hypothesis is only partially validated by the analyzed experiments.

The significance of cell survival parameters for the use of equivalent uniform dose in tumour dose evaluation

2002 ◽  
Vol 3 (1) ◽  
pp. 27-32
Author(s):  
W. Kilby
Keyword(s):  
Cell Survival ◽  
Rank Order ◽  
Treatment Plan ◽  
Survival Models ◽  
Model Parameters ◽  
Linear Quadratic ◽  
Equivalent Uniform Dose ◽  
Tumour Dose ◽  
Treatment Plans ◽  
Treatment Plan Evaluation

Equivalent Uniform Dose (EUD) has been proposed as a means of comparing treatment plans which include large PTV dose heterogeneity. Moreover, it has been suggested that EUD is insensitive to the underlying cell survival model parameters used in its calculation, and that arbitrary values might be used. This dependence of EUD on radiobiological parameters has been studied using different cell survival models (exponential and linear quadratic) and a range of artificially generated and clinical (lung and prostate) treatment plans. EUD was found to be strongly dependent on the variable SF2, but not on α/β, or number of fractions. When clinical treatment plans were ranked in order of EUD, a dependence of rank order on SF2 was observed, suggesting that arbitrary SF2 values are not appropriate for treatment plan evaluation. These results suggest that tumour specific SF2 values should be used for EUD calculation, and this is discussed.

scholarly journals A Maternal Smad Protein Regulates Early Embryonic Apoptosis in Xenopus laevis

2002 ◽  
Vol 22 (5) ◽  
pp. 1317-1328 ◽  
Author(s):  
Yuko Miyanaga ◽  
Ingrid Torregroza ◽  
Todd Evans
Keyword(s):  
Functional Analysis ◽  
Cell Survival ◽  
Caspase 3 ◽  
Embryonic Cell ◽  
Early Embryogenesis ◽  
Cell Cycles ◽  
Smad Proteins ◽  
Smad Protein ◽  
Smad Signaling Pathway ◽  
A Cell

ABSTRACT We identified cDNAs encoding the Xenopus Smad proteins most closely related to mammalian Smad8, and we present a functional analysis of this activity (also referred to recently as xSmad11). Misexpression experiments indicate that xSmad8(11) regulates pathways distinct from those regulated by the closely related xSmad1. Embryos that develop from eggs depleted of xSmad8(11) mRNA fail to gastrulate; instead, at the time of gastrulation, they initiate a widespread program of apoptosis, via a CPP32/caspase 3 pathway. Embryos that avoid this fate display gastrulation defects. Activation of apoptosis is rescued by expression of xSmad8(11) but not xSmad1. Our results demonstrate an embryonic requirement for Smad8(11) activity and show that a maternally derived Smad signaling pathway is required for gastrulation and for mediating a cell survival program during early embryogenesis. We suggest that xSmad8(11) functions as part of a maternally derived mechanism shown previously by others to monitor Xenopus early embryonic cell cycles.

Intersex-like (IXL) Is a Cell Survival Regulator in Pancreatic Cancer with 19q13 Amplification

2007 ◽  
Vol 67 (5) ◽  
pp. 1943-1949 ◽  
Author(s):  
Riina Kuuselo ◽  
Kimmo Savinainen ◽  
David O. Azorsa ◽  
Gargi D. Basu ◽  
Ritva Karhu ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Cell Survival ◽  
A Cell

scholarly journals Seasonal sea ice prediction based on regional indices

2018 ◽  
Author(s):  
John E. Walsh ◽  
J. Scott Stewart ◽  
Florence Fetterer
Keyword(s):  
Sea Ice ◽  
Chukchi Sea ◽  
Numerical Models ◽  
Linear Trend ◽  
Piecewise Linear ◽  
Severity Index ◽  
The Arctic ◽  
Linear Quadratic ◽  
Predictive Skill ◽  
Arctic Ice

Abstract. Basic statistical metrics such as autocorrelations and across-region lag correlations of sea ice variations provide benchmarks for the assessments of forecast skill achieved by other methods such as more sophisticated statistical formulations, numerical models, and heuristic approaches. However, the strong negative trend of sea ice coverage in recent decades complicates the evaluation of statistical skill by inflating the correlation of interannual variations of pan-Arctic and regional ice extent. In this study we provide a quantitative evaluation of the contribution of the trend to the predictive skill of monthly and seasonal ice extent on the pan-Arctic and regional scales. We focus on the Beaufort Sea where the Barnett Severity Index provides a metric of historical variations in ice conditions over the summer shipping season. The variance about the trend line differs little among various methods of detrending (piecewise linear, quadratic, cubic, exponential). Application of the piecewise linear trend calculation indicates an acceleration of the trend during the 1990s in most of the Arctic subregions. The Barnett Severity Index as well as September pan-Arctic ice extent show significant statistical predictability out to several seasons when the data include the trend. However, this apparent skill largely vanishes when the data are detrended. No region shows significant correlation with the detrended September pan-Arctic ice extent at lead times greater than a month or two; the concurrent correlations are strongest with the East Siberian Sea. The Beaufort Sea’s ice extent as far back as July explains about 20 % of the variance of the Barnett Severity Index, which is primarily a September metric. The Chukchi Sea is the only other region showing a significant association with the Barnett Severity Index, although only at a lead time of a month or two.

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