scholarly journals Quantitative Modeling of Carcinogenesis Induced By Single Beams Or Mixtures of Space Radiations Using Targeted And Non-Targeted Effects

2021 ◽  
Author(s):  
Igor Shuryak ◽  
Rainer K. Sachs ◽  
David J. Brenner
Keyword(s):  
Health Risks ◽  
Dose Response ◽  
Radiation Effects ◽  
Negative Binomial ◽  
Current Knowledge ◽  
Model Parameters ◽  
Radiation Quality ◽  
Biological Damage ◽  
Γ Rays ◽  
Radiation Type

Abstract Ionizing radiations encountered by astronauts on deep space missions produce biological damage by two main mechanisms: (1) Targeted effects (TE) due to direct traversals of cells by ionizing tracks. (2) Non-targeted effects (NTE) caused by release of signals from directly hit cells. The combination of these mechanisms generates non-linear dose response shapes, which need to be modeled quantitatively to predict health risks from space exploration. Here we used a TE+NTE model to analyze data on APC(1638N/+) mouse tumorigenesis induced by space-relevant doses of protons, 4He, 12C, 16O, 28Si or 56Fe ions, or γ rays. A customized weighted Negative Binomial distribution was used to describe the radiation type- and dose-dependent data variability. This approach allowed detailed quantification of dose-response shapes, NTE- and TE-related model parameters, and radiation quality metrics (relative biological effectiveness, RBE, and radiation effects ratio, RER, relative to γ rays) for each radiation type. Based on the modeled responses for each radiation type, we predicted the tumor yield for a Mars-mission-relevant mixture of these radiations, using the recently-developed incremental effect additivity (IEA) synergy theory. The proposed modeling approach can enhance current knowledge about quantification of space radiation quality effects, dose response shapes, and ultimately the health risks for astronauts.

scholarly journals Quantitative modeling of carcinogenesis induced by single beams or mixtures of space radiations using targeted and non-targeted effects

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Igor Shuryak ◽  
Rainer K. Sachs ◽  
David J. Brenner
Keyword(s):  
Health Risks ◽  
Dose Response ◽  
Radiation Effects ◽  
Negative Binomial ◽  
Current Knowledge ◽  
Model Parameters ◽  
Radiation Quality ◽  
Biological Damage ◽  
Γ Rays ◽  
Radiation Type

AbstractIonizing radiations encountered by astronauts on deep space missions produce biological damage by two main mechanisms: (1) Targeted effects (TE) due to direct traversals of cells by ionizing tracks. (2) Non-targeted effects (NTE) caused by release of signals from directly hit cells. The combination of these mechanisms generates non-linear dose response shapes, which need to be modeled quantitatively to predict health risks from space exploration. Here we used a TE + NTE model to analyze data on APC(1638N/+) mouse tumorigenesis induced by space-relevant doses of protons, 4He, 12C, 16O, 28Si or 56Fe ions, or γ rays. A customized weighted Negative Binomial distribution was used to describe the radiation type- and dose-dependent data variability. This approach allowed detailed quantification of dose–response shapes, NTE- and TE-related model parameters, and radiation quality metrics (relative biological effectiveness, RBE, and radiation effects ratio, RER, relative to γ rays) for each radiation type. Based on the modeled responses for each radiation type, we predicted the tumor yield for a Mars-mission-relevant mixture of these radiations, using the recently-developed incremental effect additivity (IEA) synergy theory. The proposed modeling approach can enhance current knowledge about quantification of space radiation quality effects, dose response shapes, and ultimately the health risks for astronauts.

scholarly journals The Double Threshold: Consequences for Identifying Low-Dose Radiation Effects

Dose-Response ◽  
2020 ◽  
Vol 18 (3) ◽  
pp. 155932582094972
Author(s):  
Alan Waltar ◽  
Ludwig Feinendegen
Keyword(s):  
Dose Response ◽  
Radiation Effects ◽  
Low Dose ◽  
Development Program ◽  
Absorbed Dose ◽  
Current Data ◽  
Whole Body ◽  
Radiation Quality ◽  
Adaptive Protection ◽  
New Research

Prior to observing low-dose-induced cell signaling and adaptive protection, radiogenic stochastic effects were assumed to be linearly related to absorbed dose. Now, abundant data prove the occurrence of radiogenic adaptive protection specifically at doses below ∼ 200 mGy (with some data suggesting such protection at a dose even higher than 200 mGy). Moreover, cells do not thrive properly when deprived of radiation below background dose. Two threshold doses need be considered in constructing a valid dose-response relationship. With doses beginning to rise from zero, cells increasingly escape radiation deprivation. The dose at which radiation-deprived cells begin to function homeostatically provides dose Threshold A. With further dose increase, adaptive protection becomes prominent and then largely disappears at acute doses above ∼ 200 mGy. The dose at which damage begins to override protection defines Threshold B. Thresholds A and B should be terms in modeling dose-response functions. Regarding whole-body responses, current data suggest for low-LET acute, non-chronic, irradiation a Threshold B of about 100 mGy prevails, except for leukemia and probably some other malignancies, and for chronic, low dose-rate irradiation where the Threshold B may well reach 1 Gy per year. A new Research and Development Program should determine individual Thresholds A and B for various radiogenic cell responses depending on radiation quality and target.

scholarly journals Resilience of Heterogeneous Aquifers Evaluated from Different Dose-Response Models of Bisphenol A

Proceedings ◽  
2019 ◽  
Vol 48 (1) ◽  
pp. 21
Author(s):  
Jinwoo Im ◽  
Calogero B. Rizzo ◽  
Felipe P. J. de Barros
Keyword(s):  
Bisphenol A ◽  
Human Health ◽  
Health Risks ◽  
Dose Response ◽  
Emerging Contaminants ◽  
Contaminated Sites ◽  
Heterogeneous Structure ◽  
Control Plane ◽  
Human Health Risks ◽  
The Impact

With the growing concerns over emerging contaminants in indirect potable reuse (IPR) applications, we investigate the impact on human health risk of emerging contaminants introduced into groundwater. Some emerging contaminants have potential endocrine-related health effects at a specific exposure range that is much lower than current guidelines. We start by analyzing Bisphenol A (BPA), which is one of the frequently detected emerging contaminants in groundwater. The objective of this study is to understand how the non-trivial toxicity of BPA affects the estimation of human health risks and, consequentially, aquifer resilience. Based on our results, we aim to provide indications on how to improve water resources management in BPA contaminated sites. We use numerical methods to model BPA contamination of a three-dimensional aquifer, and human health risks and aquifer resilience are estimated at a control plane representing an environmentally sensitive target. A Monte Carlo simulation is conducted to compute uncertainty associated with two levels of heterogeneity. In order to evaluate health risks due to BPA, two types of Dose-Response (DR) models are considered: the monotonic DR model for general exposure and the non-monotonic DR model for prenatal/postnatal exposure. The aquifer resilience is defined as the capacity to recover the state where groundwater is considered potable (i.e., negligible health risks due to BPA). When using the non-monotonic DR model, computational results indicate that the aquifer resilience reduces and its uncertainty increases as the aquifer heterogeneity increases. On the other hand, the aquifer resilience considering the monotonic DR model enhances, and its uncertainty increases relatively smaller than the one considering the non-monotonic DR model. In addition, the variability of the aquifer resilience is controlled by the residence time of the BPA plumes at the control plane, which is related to the volumetric flow rate at the front side of the contamination source. Finally, the decision-making strategy for BPA contaminated sites should be established in accordance with the heterogeneous structure of aquifer and land uses that determines which DR model of BPA is more important in estimating the aquifer resilience.

The Dose Response of Chromosome Aberrations in Human Lymphocytes InducedIn Vitroby Very Low-Dose γ Rays

2011 ◽  
Vol 175 (2) ◽  
pp. 208-213 ◽  
Author(s):  
Toshiyasu Iwasaki ◽  
Yoshio Takashima ◽  
Toshikazu Suzuki ◽  
Mitsuaki A. Yoshida ◽  
Isamu Hayata
Keyword(s):  
Dose Response ◽  
Chromosome Aberrations ◽  
Low Dose ◽  
Human Lymphocytes ◽  
Γ Rays

RADIATION-INDUCED GENOMIC INSTABILITY: RADIATION QUALITY AND DOSE RESPONSE

2003 ◽  
Vol 85 (1) ◽  
pp. 23-29 ◽  
Author(s):  
Leslie E. Smith ◽  
Shruti Nagar ◽  
Grace J. Kim ◽  
William F. Morgan
Keyword(s):  
Genomic Instability ◽  
Dose Response ◽  
Radiation Quality ◽  
Radiation Induced

A critical review on the potential impacts of neonicotinoid insecticide use: current knowledge of environmental fate, toxicity, and implications for human health

2020 ◽  
Vol 22 (6) ◽  
pp. 1315-1346 ◽  
Author(s):  
Darrin A. Thompson ◽  
Hans-Joachim Lehmler ◽  
Dana W. Kolpin ◽  
Michelle L. Hladik ◽  
John D. Vargo ◽  
...  
Keyword(s):  
Human Health ◽  
Health Risks ◽  
Critical Review ◽  
Human Exposure ◽  
Environmental Fate ◽  
Current Knowledge ◽  
Neonicotinoid Insecticides ◽  
Neonicotinoid Insecticide

The review examines literature relevant to environmental fate, transformation, and toxicity, and human exposure and health risks of neonicotinoid insecticides.

scholarly journals Construction of A New Dose–Response Model for Staphylococcus aureus Considering Growth and Decay Kinetics on Skin

Pathogens ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 253 ◽  
Author(s):  
Esfahanian ◽  
Adhikari ◽  
Dolan ◽  
Mitchell
Keyword(s):  
Staphylococcus Aureus ◽  
Dose Response ◽  
Sensitivity Coefficient ◽  
Ordinary Least Squares ◽  
Exposure Dose ◽  
Human Infection ◽  
Model Parameters ◽  
Response Model ◽  
Least Squares Regression ◽  
Decay Kinetics

. In order to determine the relationship between an exposure dose of Staphylococcus aureus (S. aureus) on the skin and the risk of infection, an understanding of the bacterial growth and decay kinetics is very important. Models are essential tools for understanding and predicting bacterial kinetics and are necessary to predict the dose of organisms post-exposure that results in a skin infection. One of the challenges in modeling bacterial kinetics is the estimation of model parameters, which can be addressed using an inverse problem approach. The objective of this study is to construct a microbial kinetic model of S. aureus on human skin and use the model to predict concentrations of S. aureus that result in human infection. In order to model the growth and decay of S. aureus on skin, a Gompertz inactivation model was coupled with a Gompertz growth model. A series of analyses, including ordinary least squares regression, scaled sensitivity coefficient analysis, residual analysis, and parameter correlation analysis were conducted to estimate the parameters and to describe the model uncertainty. Based on these analyses, the proposed model parameters were estimated with high accuracy. The model was then used to develop a new dose-response model for S. aureus using the exponential dose–response model. The new S. aureus model has an optimized k parameter equivalent to 8.05 × 10−8 with 95th percentile confidence intervals between 6.46 × 10−8 and 1.00 × 10−7.

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