Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
In the domains of medicine and space exploration, refining risk assessment models for protecting healthy tissue from ionizing radiation is crucial. Understanding radiation-induced effects requires biological experimentations at the cellular population level and the cellular scale modeling using Monte Carlo track structure codes. We present MINAS TIRITH, a tool using Geant4-DNA Monte Carlo-generated databases to study DNA damage distribution at the cell population scale. It introduces a DNA damage location module and proposes a method to convert double-strand breaks (DSB) into DNA Damage Response foci. We evaluate damage location precision and DSB-foci conversion parameters. MINAS TIRITH's accuracy is validated against-H2AX foci distribution from cell population exposed to monoenergetic neutron beams (2.5 or 15.1 MeV) under different configurations, yielding mixed radiation fields. Strong agreement between simulation and experimental results was found demonstrating MINAS TIRITH's predictive precision in radiation-induced DNA damage topology. Additionally, modeling intercellular damage variability within a population subjected to a specific macroscopic dose identifies subpopulations, enhancing realistic fate models. This approach advances our understanding of radiation-induced effects on cellular systems for risk assessment improvement.
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Source |
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http://dx.doi.org/10.1088/1361-6560/ad043d | DOI Listing |
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