{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T23:54:39Z","timestamp":1791244479624,"version":"4.1.0"},"reference-count":48,"publisher":"Radiation Research Society","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Radiation Research"],"published-print":{"date-parts":[[2025,6,6]]},"abstract":"<jats:p>The radiation environment in space consists of a complex mixture of particles and energies that are characteristically different from any natural Earth radiation source. Projections of space radiation cancer risk are obtained by scaling or adjusting epidemiological models derived from terrestrially exposed cohorts to account for differences in radiation quality, dose rate, and other factors. Radiation quality and dose-rate effects introduce significant uncertainty, thereby obfuscating risk communication and hindering the ability to evaluate the efficacy of mitigation strategies such as medical countermeasures. Space radiation quality factors are developed through a multi-step process that requires computational models and experimental data. The first step in this process involves developing dose-response models and fitting them to data from ground-based experiments involving acute irradiation of animals or cells. There is limited ground-based data compared to the range of ions and energies found in space; thus, dose-response models must be able to reproduce available data and predict responses where no data exist. This work focuses on developing a microdosimetric (\u00b5D) dose-response model applicable to experimental datasets relevant to space radiation cancer induction. Three experimental datasets, encompassing murine Harderian gland tumorigenesis and chromosome aberrations in human skin fibroblasts and blood lymphocytes, are utilized to demonstrate key features and overall performance of the \u00b5D model. The model generates non-linear dose-responses and can predict charge and energy dependence observed in experimental data without the use of empirical functions or corrections. Additionally, the \u00b5D model identifies the critical microscopic target population and target size that drive the observed biological effects.<\/jats:p>","DOI":"10.1667\/rade-25-00021.1","type":"journal-article","created":{"date-parts":[[2025,6,6]],"date-time":"2025-06-06T05:03:51Z","timestamp":1749186231000},"page":"81-100","source":"Crossref","is-referenced-by-count":5,"title":["A Microdosimetric Dose Response Model for Monoenergetic Ions and Doses Relevant for Space Radiation Carcinogenesis"],"prefix":"10.1667","volume":"204","author":[{"given":"T. C.","family":"Slaba","sequence":"first","affiliation":[{"name":"NASA Langley Research Center"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"F.","family":"Poignant","sequence":"additional","affiliation":[{"name":"Analytical Mechanics Associates; Hampton, Virginia 23666"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S.","family":"Rahmanian","sequence":"additional","affiliation":[{"name":"Analytical Mechanics Associates; Hampton, Virginia 23666"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1243","reference":[{"key":"1","doi-asserted-by":"crossref","unstructured":"ZS Patel, TJ Brunstetter, WJ Tarver, et al.  \"npj Microgravity.\"  6, \"Red risks for a journal to the red planet: The highest priority human health risks for a mission to Mars.\" 1 (2020)","DOI":"10.1038\/s41526-020-00124-6"},{"key":"2","doi-asserted-by":"crossref","unstructured":"JD. Boice,  \"Int. J. Radiat. Biol.\"  98, \"The Million Person Study relevance to space exploration and Mars.\" 551 (2022)","DOI":"10.1080\/09553002.2019.1589020"},{"key":"4","unstructured":"FA Cucinotta, MY Kim, LJ Chappell,  \"NASA TP 2013-207375.\"  \"Space radiation cancer risk projections and uncertainties \u2013 2012.\" (2013)"},{"key":"5","unstructured":"\"Space Radiation and Astronaut Health: Managing and Communicating Cancer Risks.\"  2021"},{"key":"6","doi-asserted-by":"crossref","unstructured":"WS Dynan, PY Chang, BJ Sishc, et al.  \"Life Sci. Space Res.\"  35, \"Breaking the limit: biological countermeasures for space radiation exposure to enable long-duration spaceflight.\" 1 (2022)","DOI":"10.1016\/j.lssr.2022.10.003"},{"key":"7","doi-asserted-by":"crossref","unstructured":"CM Werneth, TC Slaba, SR Blattnig, et al.  \"Life Sci. Space Res.\"  25, \"A methodology for investigating the impact of biological countermeasures on the risk of exposure induced death.\" 72 (2020)","DOI":"10.1016\/j.lssr.2020.03.001"},{"key":"8","doi-asserted-by":"crossref","unstructured":"CM Werneth, TC Slaba, JL Huff, et al.  \"Health Phys.\"  123, \"Medical countermeasure requirements to meet NASA's space radiation permissible exposure limits for a Mars mission scenario.\" 116 (2022)","DOI":"10.1097\/HP.0000000000001572"},{"key":"9","unstructured":"\"NCRP Report 107.\"  \"The relative biological effectiveness of radiations of different quality.\" (1990)"},{"key":"11","doi-asserted-by":"crossref","unstructured":"K George, M Durante, V Willingham, et al.  \"Radiat Res.\"  160, \"Biological effectiveness of accelerated particles for the induction of chromosome damage measured in metaphase and inter-phase human lymphocytes.\" 425 (2003)","DOI":"10.1667\/RR3064"},{"key":"12","doi-asserted-by":"crossref","unstructured":"K George  and FA Cucinotta  \"Adv. Space Res.\"  39, \"The influence of shielding on the biological effectiveness of accelerated particles for the induction of chromosome damage.\" 1076 (2007)","DOI":"10.1016\/j.asr.2007.01.004"},{"key":"15","doi-asserted-by":"crossref","unstructured":"LJ Chappell, SR Elgart, CM Milder, et al.  \"Radiat Res.\"  194, \"Assessing nonlinearity in harderian gland tumor induction using three combined HZE-irradiated mouse datasets.\" 38 (2020)","DOI":"10.1667\/RR15539.1"},{"key":"16","doi-asserted-by":"crossref","unstructured":"I Shuryak, TC Slaba, I Plante, et al.  \"Sci. Rep.\"  12, \"A practical approach for continuous in situ characterization of radiation quality factors in space.\" 1 (2022)","DOI":"10.1038\/s41598-022-04937-1"},{"key":"18","doi-asserted-by":"crossref","unstructured":"TC Slaba, SR Blattnig, JW Norbury, et al.  \"Life Sci. Space Res.\"  8, \"Reference field specification and preliminary beam selection strategy for accelerator-based GCR simulation\" 52 (2016)","DOI":"10.1016\/j.lssr.2016.01.001"},{"key":"19","doi-asserted-by":"crossref","unstructured":"LC Simonsen, TC Slaba, P Guida, et al.  \"Plos Biology.\"  18, \"NASA's first ground-based galactic cosmic ray simulator: enabling a new era in space radiobiology research.\" e3000669 (2020)","DOI":"10.1371\/journal.pbio.3000669"},{"key":"20","doi-asserted-by":"crossref","unstructured":"RJM Fry, P Powers-Risius, EL Alpen, et al.  \"Radiat Res.\"  104, \"High-LET radiation carcinogenesis.\" 188 (1985)","DOI":"10.2307\/3576646"},{"key":"22","doi-asserted-by":"crossref","unstructured":"FA Cucinotta  and E Cacao  \"Sci. Rep.\"  7, \"Non-targeted effects models predict significantly higher Mars mission cancer risk than targeted effects models.\" 1 (2017)","DOI":"10.1038\/s41598-017-02087-3"},{"key":"23","unstructured":"\"International Commission on Radiation Units and Measurements Report 36. Microdosimetry.\"  (1983)"},{"key":"24","unstructured":"\"International Commission on Radiation Units and Measurements Report 98. Stochastic Nature of Radiation Interactions: Microdosimetry.\"  (2023)"},{"key":"25","doi-asserted-by":"crossref","unstructured":"R Taleei, S Rahmanian, H Nikjoo,  \"Radiat Res.\"  202, \"Modelling cellular response to ionizing radiation: mechanistic, semi-mechanistic, and phenomenological approaches \u2013 a historical perspective.\" 143 (2024)","DOI":"10.1667\/RADE-24-00019.1"},{"key":"26","doi-asserted-by":"crossref","unstructured":"T Els\u00e4sser, WK Weyrather, T Friedrich, et al.  \"Int. J. Radiat. Oncol. Biol. Phys.\"  78, \"Quantification of the relative biological effectiveness for ion beam radiotherapy: direct experimental comparison of proton and carbon ion beams and a novel approach for treatment planning.\" 1177 (2010)","DOI":"10.1016\/j.ijrobp.2010.05.014"},{"key":"27","doi-asserted-by":"crossref","unstructured":"T Friedrich, U Scholz, T Els\u00e4sser, et al.  \"Int. J. Radiat. Biol.\"  88, \"Calculation of the biological effects of ion beams based on the microscopic spatial damage distribution pattern.\" 103 (2012)","DOI":"10.3109\/09553002.2011.611213"},{"key":"28","doi-asserted-by":"crossref","unstructured":"RB. Hawkins,  \"Int. J. Radiat. Biol.\"  69, \"A microdosimetric-kinetic model of cell death from exposure to ionizing radiation of any LET, with experimental and clinical applications.\" 739 (1996)","DOI":"10.1080\/095530096145481"},{"key":"29","doi-asserted-by":"crossref","unstructured":"A Parisi, CJ Beltran, KM Furutani,  \"Phys. Med. Bio.\"  67, \"The Mayo Clinic Florida microdosimetric kinetic model of clonogenic survival: formalism and first benchmark against in vitro and in silico data.\" 185013 (2022)","DOI":"10.1088\/1361-6560\/ac7375"},{"key":"30","doi-asserted-by":"crossref","unstructured":"F Ballarini, S Altieri, S Bortolussi, et al.  \"Radiat. Environ. Biophys.\"  53, \"The BIANCA model\/code of radiation-induced cell death: application to human cells exposed to different radiation types.\" 525 (2014)","DOI":"10.1007\/s00411-014-0537-6"},{"key":"31","doi-asserted-by":"crossref","unstructured":"SA Kalospyros, Z Nikitaki, I Kyriakou, et al.  \"Molecules.\"  26, \"A Mathematical Radiobiological Model MRM.to predict complex DNA damage and cell survival for ionizing particle radiations of varying quality.\" 1 (2021)","DOI":"10.3390\/molecules26040840"},{"key":"33","doi-asserted-by":"crossref","unstructured":"M Alcocer-\u00c1vila, C Monini, M Cunha, et al.  \"Front. Phys.\"  10, \"Cell survival prediction in hadrontherapy with the NanOx biophysical model.\" 1011063 (2022)","DOI":"10.3389\/fphy.2022.1011063"},{"key":"35","doi-asserted-by":"crossref","unstructured":"R. Katz,  \"Nuc. Track Det.\"  2, \"Track structure theory in radiobiology and in radiation detection.\" 1 (1978)","DOI":"10.1016\/0145-224X(78)90002-9"},{"key":"36","doi-asserted-by":"crossref","unstructured":"R. Katz,  \"Adv. Space Res.\"  6, \"Biological effects of heavy ions from the standpoint of target theory.\" 191 (1986)","DOI":"10.1016\/0273-1177(86)90292-9"},{"key":"37","doi-asserted-by":"crossref","unstructured":"M. Zaider,  \"Health Phys.\"  70, \"Microdosimetric-based risk factors for radiation received in space activities during a trip to Mars.\" 845 (1996)","DOI":"10.1097\/00004032-199606000-00010"},{"key":"38","doi-asserted-by":"crossref","unstructured":"F Villegas, N Tilly, A Ahnesjo,  \"Radiat Res.\"  190, \"Target size variation in microdosimetric distributions and its impact on the linear-quadratic parameterization of cell survival.\" 504 (2018)","DOI":"10.1667\/RR15089.1"},{"key":"39","doi-asserted-by":"crossref","unstructured":"FA. Cucinotta,  \"Life Sci. Space Res.\"  40, \"Non-targeted effects and space radiation risks for astronauts on multiple International Space Station and lunar missions.\" 166 (2024)","DOI":"10.1016\/j.lssr.2023.08.003"},{"key":"40","doi-asserted-by":"crossref","unstructured":"I Plante  and FA Cucinotta  \"Monte-Carlo Simulation of Ionizing Radiation Tracks in Applications of Monte Carlo Methods in Biology, Medicine and Other Fields of Science.\"  315 (2011)","DOI":"10.5772\/15674"},{"key":"41","unstructured":"H. Barkas,  \"Nuclear Research Emulsions. Vol. 1.\"  (1963)"},{"key":"42","doi-asserted-by":"crossref","unstructured":"TC Slaba, JW Wilson, CM Werneth, et al.  \"Life Sci. Space Res.\"  27, \"Updated deterministic radiation transport for future deep space missions.\" 6 (2020)","DOI":"10.1016\/j.lssr.2020.06.004"},{"key":"43","doi-asserted-by":"crossref","unstructured":"JN Lucas, M Poggensee, T Straume,  \"Cytogenet. Cell. Genet.\"  60, \"The persistence of chromosome translocations in a radiation worker accidentally exposed to tritium.\" 255 (1992)","DOI":"10.1159\/000133353"},{"key":"44","doi-asserted-by":"crossref","unstructured":"RB Norman  and SR Blattnig  \"J. Comp. Phys.\"  233, \"Validation of nuclear models used in space radiation shielding applications.\" 464 (2013)","DOI":"10.1016\/j.jcp.2012.09.006"},{"key":"46","doi-asserted-by":"crossref","unstructured":"RB Dickinson  and TP Lele  \"Front. Cell Dev. Biol.\"  11, \"Nuclear shapes are geometrically determined by the excess surface area of the nuclear lamina.\" 1058727 (2023)","DOI":"10.3389\/fcell.2023.1058727"},{"key":"47","doi-asserted-by":"crossref","unstructured":"F Poignant, IP Plante, ZS Patel, et al.  \"Int. J. Mol. Sci.\"  23, \"Size and shape matter: geometrical properties of the nucleus and chromosome intermingling are major parameters of chromosome aberration formation.\" 8638 (2022)","DOI":"10.3390\/ijms23158638"},{"key":"48","unstructured":"BW. Silverman,  \"Density estimation for statistics and data analysis.\"  45 (1986)"},{"key":"32","doi-asserted-by":"crossref","unstructured":"DJ Carlson, RD Stewart, VA Semenenko, et al.  \"Radiat Res.\"  169, \"Combined use of Monte Carlo DNA damage simulations and deterministic repair models to examine putative mechanisms of cell killing.\" 447 (2008)","DOI":"10.1667\/RR1046.1"},{"key":"14","doi-asserted-by":"crossref","unstructured":"M Hada, LJ Chappell, M Wang, et al.  \"Radiat Res.\"  182, \"Induction of chromosomal aberrations at fluences of less than one HZE particle per cell nucleus.\" 368 (2014)","DOI":"10.1667\/RR13721.1"},{"key":"13","doi-asserted-by":"crossref","unstructured":"K George, M Hada, L Chappell, et al.  \"Radiat Res.\"  180, \"Biological effectiveness of accelerated particles for the induction of chromosome damage: Track structure effects.\" 25 (2013)","DOI":"10.1667\/RR3291.1"},{"key":"34","doi-asserted-by":"crossref","unstructured":"R Katz, B Ackerson, M Homayoonfar, et al.  \"Radiat Res.\"  47, \"Inactivation of cells by heavy ion bombardment.\" 402 (1971)","DOI":"10.2307\/3573247"},{"key":"3","doi-asserted-by":"crossref","unstructured":"EJ Grant, A Brenner, H Sugiyama, et al.  \"Radiat Res.\"  187, \"Solid cancer incidence among the Life Span Study of Atomic Bomb Survivors: 1958\u20132009.\" 513 (2017)","DOI":"10.1667\/RR14492.1"},{"key":"21","doi-asserted-by":"crossref","unstructured":"EL Alpen, P Powers-Risius, SB Curtis, et al.  \"Radiat Res.\"  136, \"Tumorigenic potential of high-Z, high-LET charged-particle radiations.\" 382 (1993)","DOI":"10.2307\/3578551"},{"key":"45","doi-asserted-by":"crossref","unstructured":"BM Skinner  and EEP Johnson  \"Chromosoma.\"  126, \"Nuclear morphologies: their diversity and functional relevance.\" 195 (2017)","DOI":"10.1007\/s00412-016-0614-5"},{"key":"17","doi-asserted-by":"crossref","unstructured":"PY Chang, FA Cucinotta, KA Bjornstad, et al.  \"Radiat Res.\"  185, \"Harderian gland tumorigenesis: low-dose and LET response.\" 449 (2016)","DOI":"10.1667\/RR14335.1"},{"key":"10","doi-asserted-by":"crossref","unstructured":"I Shuryak, AJ Fornace, K Datta, et al.  \"Radiat Res.\"  187, \"Scaling human cancer risks from low LET to high LET when dose-effect relationships are complex.\" 486 (2017)","DOI":"10.1667\/RR009CC.1"}],"container-title":["Radiation Research"],"original-title":[],"link":[{"URL":"https:\/\/meridian.allenpress.com\/radiation-research\/article-pdf\/doi\/10.1667\/RADE-25-00021.1\/3521300\/10.1667_rade-25-00021.1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/meridian.allenpress.com\/radiation-research\/article-pdf\/doi\/10.1667\/RADE-25-00021.1\/3521300\/10.1667_rade-25-00021.1.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T23:12:48Z","timestamp":1791241968000},"score":1,"resource":{"primary":{"URL":"https:\/\/bioone.org\/journals\/radiation-research\/volume-204\/issue-2\/RADE-25-00021.1\/A-Microdosimetric-Dose-Response-Model-for-Monoenergetic-Ions-and-Doses\/10.1667\/RADE-25-00021.1.full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,6]]},"references-count":48,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2025,8,1]]}},"URL":"https:\/\/doi.org\/10.1667\/rade-25-00021.1","relation":{},"ISSN":["0033-7587","1938-5404"],"issn-type":[{"value":"0033-7587","type":"print"},{"value":"1938-5404","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,6]]}}}