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Relationship: 1982


The title of the KER should clearly define the two KEs being considered and the sequential relationship between them (i.e., which is upstream and which is downstream). Consequently all KER titles take the form “upstream KE leads to downstream KE”.  More help

Energy Deposition leads to Increase, Chromosomal aberrations

Upstream event
Upstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help
Downstream event
Downstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes. Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

This table is automatically generated upon addition of a KER to an AOP. All of the AOPs that are linked to this KER will automatically be listed in this subsection. Clicking on the name of the AOP in the table will bring you to the individual page for that AOP. More help
AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
Direct deposition of ionizing energy leading to lung cancer non-adjacent High High Vinita Chauhan (send email) Under development: Not open for comment. Do not cite EAGMST Under Review

Taxonomic Applicability

Select one or more structured terms that help to define the biological applicability domain of the KER. In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER. Authors can indicate the relevant taxa for this KER in this subsection. The process is similar to what is described for KEs (see pages 30-31 and 37-38 of User Handbook) More help
Term Scientific Term Evidence Link
human Homo sapiens High NCBI
mouse Mus musculus High NCBI
rat Rattus norvegicus High NCBI

Sex Applicability

Authors can indicate the relevant sex for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of the User Handbook). More help
Sex Evidence
Unspecific High

Life Stage Applicability

Authors can indicate the relevant life stage for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of User Handbook). More help
Term Evidence
All life stages High

Key Event Relationship Description

Provide a brief, descriptive summation of the KER. While the title itself is fairly descriptive, this section can provide details that aren’t inherent in the description of the KEs themselves (see page 39 of the User Handbook). This description section can be viewed as providing the increased specificity in the nature of upstream perturbation (KEupstream) that leads to a particular downstream perturbation (KEdownstream), while allowing the KE descriptions to remain generalised so they can be linked to different AOPs. The description is also intended to provide a concise overview for readers who may want a brief summation, without needing to read through the detailed support for the relationship (covered below). Careful attention should be taken to avoid reference to other KEs that are not part of this KER, other KERs or other AOPs. This will ensure that the KER is modular and can be used by other AOPs. More help

Energy can be deposited on biomolecules from various forms of radiation in a randomized manner. Radiation with high linear energy transfer (LET) tends to produce more complex, dense structural damage than low LET radiation; both, however, can lead to detrimental damage within a cell (Hada and Georgakilas 2008; Okayasu 2012; Lorat et al. 2015; Nikitaki et al. 2016). The DNA is particularly susceptible to damage in the form of DNA strand breaks.  This damaged DNA can lead to aberrations/rearrangements in chromosomes and chromatids. Examples of chromosome-type aberrations include chromosome-type breaks, ring chromosomes, and dicentric chromosomes, while chromatid-type aberrations refer to chromatid-type breaks and chromatid exchanges (Hagmar et al. 2004; Bonassi et al. 2008). Other types of CAs that may occur in response to radiation include micronuclei (MN), nucleoplasmic bridges (NPBs), and copy number variants (CNVs). CAs may also be classified as stable aberrations (translocations, inversions, insertions and deletions) and unstable aberrations (dicentric chromosomes, acentric fragments, centric rings and MN) (Hunter and Muirhead 2009; Qian et al. 2016)

Evidence Supporting this KER

Assembly and description of the scientific evidence supporting KERs in an AOP is an important step in the AOP development process that sets the stage for overall assessment of the AOP (see pages 49-56 of the User Handbook). To do this, biological plausibility, empirical support, and the current quantitative understanding of the KER are evaluated with regard to the predictive relationships/associations between defined pairs of KEs as a basis for considering WoE (page 55 of User Handbook). In addition, uncertainties and inconsistencies are considered. More help
Biological Plausibility
Define, in free text, the biological rationale for a connection between KEupstream and KEdownstream. What are the structural or functional relationships between the KEs? For example, there is a functional relationship between an enzyme’s activity and the product of a reaction it catalyses. Supporting references should be included. However, it is recognised that there may be cases where the biological relationship between two KEs is very well established, to the extent that it is widely accepted and consistently supported by so much literature that it is unnecessary and impractical to cite the relevant primary literature. Citation of review articles or other secondary sources, like text books, may be reasonable in such cases. The primary intent is to provide scientifically credible support for the structural and/or functional relationship between the pair of KEs if one is known. The description of biological plausibility can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured (see page 40 of the User Handbook for further information).   More help

The biological plausibility for this KER is strong, as there is a broad mechanistic understanding of the process CA induction from deposited energy in the form of radiation, which is widely accepted. Many studies have provided clear evidence to support this KER using both in vitro and in vivo models (Schmid et al. 2002; Thomas et al. 2003; Maffei et al. 2004; Tucker et al. 2005b; Tucker et al. 2005a; George et al. 2009; Meenakshi and Mohankumar 2013; Santovito et al. 2013; Arlt et al. 2014; Balajee et al. 2014; George et al. 2014; Han et al. 2014; Vellingiri et al. 2014; Suto et al. 2015; Adewoye et al. 2015; Cheki et al. 2016; Mcmahon et al. 2016; Morishita et al. 2016; Qian et al. 2016; Basheerudeen et al. 2017; Meenakshi et al. 2017; Abe et al. 2018; Jang et al. 2019; Puig et al., 2016; Barquinero et al., 2004; Curwen et al., 2012; Testa et al., 2018; Franken et al., 2012; Cornforth et al., 2002; Loucas et al., 2013; Nagasawa et al., 1990a; Nagasawa et al., 1990b; Edwards et al., 1980; Themis et al., 2013; Schmid et al., 1996; Mestres et al., 2004; Bilbao et al., 1989; Mill et al., 1996; Brooks, 1975; Tawn and Thierens, 2009; Durante et al., 1992; Hamza and Mohankumar, 2009; Takatsuji and Sasaki, 1984; Moquet et al., 2001; Purrott et al., 1980; duFrain et al., 1979).

The process from deposition of energy to CA occurrence has been described in several reviews (Smith et al. 2003; Christensen 2014; Sage and Shikazono 2017). When ionizing radiation comes into contact with a cell, it is able to deposit energy through ionization and excitation of molecules, which results in the freeing of electrons. These electrons have enough energy to break chemical bonds; thus if the high-energy electrons come into contact with DNA, they may break DNA bonds and cause damage in the form of double-strand breaks, single-strand breaks, base damage, or the crosslinking of DNA to other molecules. This damage should trigger DNA repair. If the enzymatic repair, however, is incorrect or incomplete, this could push the cell towards apoptotic pathways. However, the repair processes may lead to asymmetrical exchanges in the chromosomes that are not removed from the cell and can propagate in the form of aberrations. Radiation-damaged cells display accumulated CAs  in the form of chromosomal rearrangements, genetic amplifications and/or MN (Smith et al. 2003; Christensen 2014; Sage and Shikazono 2017).  

The first incidence of radiation-induced CA was reported by Weissenborn and Streffer (1988).  The authors show formation of CAs in neutron and X-irradiated mouse embryos, subsequent studies by numerous laboratories have shown CA formation from different radiation qualities (reviewed by Smith et al, 2003).  More recent studies also support this notion.  A study using a single particle irradiation system (SPICE) to deliver highly directed and tightly controlled radiation doses to select nuclei of oral squamous cell carcinoma cells was shown to generate 46 mutant monoclonal sublines. Copy number alterations ((CNAs), which are CNVs found in somatic cells rather than germline cells (Li et al. 2009)), were found in 43 (93%) of the sublines generated. Although most of the sublines were found to have multiple CNAs, one subline in particular had 16 documented CNAs. Further genetic analyses of this subline revealed 14 de novo chromosomal rearrangements and 2 detectable translocations in addition to the 16 CNAs, which is suggestive of chromothripsis. This study thus provides strong evidence that direct deposition of energy by ionizing radiation results in CAs, and in some cases, chromothripsis (Morishita et al. 2016).

CNVs may also be generated through deposition of energy by ionizing radiation. Due to the structural similarities between CNVs that are radiation-induced, chemically-induced, and spontaneously-occurring, all CNVs are likely produced by a similar mechanism. The chemicals, aphidicolin and hydroxyurea, are known inducers of DNA replication stress. This suggests that radiation-induced CNVs are also formed through a similar replication-dependent mechanism(Arlt et al. 2014). Additionally, CNVs may affect germline cells. In fact, there was a significant 8-fold increase in de novo CNVs in the progeny of irradiated male mice, regardless of whether the radiation affected post-meiotic sperm or pre-meiotic sperm. The majority of these CNVs were found to be large deletions, often more than 1000 kB (Adewoye et al. 2015).

Uncertainties and Inconsistencies
In addition to outlining the evidence supporting a particular linkage, it is also important to identify inconsistencies or uncertainties in the relationship. Additionally, while there are expected patterns of concordance that support a causal linkage between the KEs in the pair, it is also helpful to identify experimental details that may explain apparent deviations from the expected patterns of concordance. Identification of uncertainties and inconsistencies contribute to evaluation of the overall WoE supporting the AOPs that contain a given KER and to the identification of research gaps that warrant investigation (seep pages 41-42 of the User Handbook).Given that AOPs are intended to support regulatory applications, AOP developers should focus on those inconsistencies or gaps that would have a direct bearing or impact on the confidence in the KER and its use as a basis for inference or extrapolation in a regulatory setting. Uncertainties that may be of academic interest but would have little impact on regulatory application don’t need to be described. In general, this section details evidence that may raise questions regarding the overall validity and predictive utility of the KER (including consideration of both biological plausibility and empirical support). It also contributes along with several other elements to the overall evaluation of the WoE for the KER (see Section 4 of the User Handbook).  More help

Uncertainties and inconsistencies in this KER are as follows:

  1. (Bender et al. 1988; Suzuki and Hei 1996; Guerrero-Carbajal et al. 2003; Day et al. 2007, Smithe et al. 2003).
Response-response Relationship
This subsection should be used to define sources of data that define the response-response relationships between the KEs. In particular, information regarding the general form of the relationship (e.g., linear, exponential, sigmoidal, threshold, etc.) should be captured if possible. If there are specific mathematical functions or computational models relevant to the KER in question that have been defined, those should also be cited and/or described where possible, along with information concerning the approximate range of certainty with which the state of the KEdownstream can be predicted based on the measured state of the KEupstream (i.e., can it be predicted within a factor of two, or within three orders of magnitude?). For example, a regression equation may reasonably describe the response-response relationship between the two KERs, but that relationship may have only been validated/tested in a single species under steady state exposure conditions. Those types of details would be useful to capture.  More help

There is evidence of a positive response-response relationship between the radiation dose and the frequency of CAs (Schmid et al. 2002; Thomas et al. 2003; Tucker et al. 2005a; Tucker et al. 2005b; George et al. 2009; Arlt et al. 2014; Balajee et al. 2014; Suto et al. 2015; Mcmahon et al. 2016; Abe et al. 2018; Jang et al. 2019). Most studies found that the response-response relationship was linear-quadratic (Schmid et al. 2002; Suto et al. 2015; Abe et al. 2018; Jang et al. 2019). One study, however, reported different results when CAs were examined across five cell lines that had been irradiated with either iron nuclei or gamma-rays. For complex aberrations in three types of fibroblasts (two of which were deficient in DNA repair), the best fit was a quadratic relationship for both gamma-rays and iron ions; for simple aberrations induced by iron ions in these cells, there was a linear relationship found. In two tumor cell lines, a linear response was defined for simple aberrations for both types of radiation, while the response for complex aberrations was not well-defined by the models that were evaluated (George et al. 2009).

This sub-section should be used to provide information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). This can be useful information both in terms of modelling the KER, as well as for analyzing the critical or dominant paths through an AOP network (e.g., identification of an AO that could kill an organism in a matter of hours will generally be of higher priority than other potential AOs that take weeks or months to develop). Identification of time-scale can also aid the assessment of temporal concordance. For example, for a KER that operates on a time-scale of days, measurement of both KEs after just hours of exposure in a short-term experiment could lead to incorrect conclusions regarding dose-response or temporal concordance if the time-scale of the upstream to downstream transition was not considered. More help

The time scale relationship between radiation exposure and the frequency of CAs has been examined. Most studies search for CAs hours, days, weeks, or even years after exposure to radiation (Schmid et al. 2002; Thomas et al. 2003; Tucker et al. 2005a; Tucker et al. 2005b; George et al. 2009; Meenakshi and Mohankumar 2013; Arlt et al. 2014; Balajee et al. 2014; Han et al. 2014; Suto et al. 2015; Cheki et al. 2016; Mcmahon et al. 2016; Basheerudeen et al. 2017; Meenakshi et al. 2017; Abe et al. 2018; Jang et al. 2019) ; this makes it particularly difficult to identify CA induction in relation to the deposition of energy by ionizing radiation. There is an account, however, of CAs appearing within 20 minutes of irradiation, with levels peaking at 40 minutes and plateauing for the remainder of the experiment (up to 100 minutes) (Mcmahon et al. 2016). CAs have also been documented 2 - 3 hours after radiation exposure, with frequency being shown to increase slightly at 24 hours (Basheerudeen et al. 2017). A study examining CAs in human blood samples for 2 - 7 days following irradiation with gamma-rays found that CAs were present at the 2-day mark, but had declined by day 7 (Tucker et al. 2005a; Tucker et al. 2005b) to suspected asymptotic minimum levels  (Tucker et al. 2005b). For translocations specifically, the relationship between time and translocation frequency was found to be linear at low doses (0 - 0.5 Gy) and linear quadratic at higher doses (0.5 - 4 Gy) (Tucker et al. 2005b). The sharpest decline over the 7 days was found in dicentrics, acentric fragments, and ring chromosomes (Tucker et al. 2005a).

Interestingly, in vivo radiation exposure has been shown to induce long-lasting CAs in a relatively short time-frame. When lymphocytes from patients undergoing an interventional radiology procedure were compared pre-procedure and 2-3 hours post-procedure, there were significant increases in chromatid-type aberrations, chromosome-type aberrations, dicentrics and MN in post-procedure lymphocytes)(Basheerudeen et al. 2017). Similarly, lymphocytes from subjects exposed to radiation 32-41 years prior to blood collection were found to have significantly increased chromosome-type aberrations (acentric fragments, dicentrics and translocations) and MN relative to unexposed controls (Han et al. 2014). Taken together, the results from these two studies suggest that CAs are not only induced within mere hours of radiation exposure, but that these radiation-induced CAs may also endure for several decades.

Known modulating factors
This sub-section presents information regarding modulating factors/variables known to alter the shape of the response-response function that describes the quantitative relationship between the two KEs (for example, an iodine deficient diet causes a significant increase in the slope of the relationship; a particular genotype doubles the sensitivity of KEdownstream to changes in KEupstream). Information on these known modulating factors should be listed in this subsection, along with relevant information regarding the manner in which the modulating factor can be expected to alter the relationship (if known). Note, this section should focus on those modulating factors for which solid evidence supported by relevant data and literature is available. It should NOT list all possible/plausible modulating factors. In this regard, it is useful to bear in mind that many risk assessments conducted through conventional apical guideline testing-based approaches generally consider few if any modulating factors. More help

As evidenced in chronic exposure studies, the relationship between CAs and radiation may be affected by sex, age and smoking status. In terms of sex, females were found to have increased aberrant cells and chromosome breaks relative to males (Maffei et al. 2004). Additionally, increases in age were associated with increased CAs, including sister chromatid exchanges per number of metaphases (Santovito et al. 2013) and MN (Vellingiri et al. 2014). Smoking was also found to increase chromosomal damage. Aberrant cells and chromosome breaks were found to be significantly increased in smokers relative to non-smokers (Maffei et al. 2004). Likewise, blood samples from smokers that were exposed to radon gas had lymphocytes with significantly increased dicentric aberrations, acentric fragments, chromatid breaks (Meenakshi and Mohankumar 2013), MN, and NPBs (Meenakshi et al. 2017) relative to lymphocytes from non-smokers also exposed to radon gas.

In vitro studies found that hyperthermia modified the effect of radiation on CA induction. In cells exposed to hyperthermic conditions (41oC for one hour) followed by radiation (4 Gy), there were significant increases in chromosomal translocations and chromosomal fragments at one hour and at 24 hours post-exposure, respectively, as compared to cells exposed only to radiation (Bergs et al. 2016).

Known Feedforward/Feedback loops influencing this KER
This subsection should define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits? In some cases where feedback processes are measurable and causally linked to the outcome, they should be represented as KEs. However, in most cases these features are expected to predominantly influence the shape of the response-response, time-course, behaviours between selected KEs. For example, if a feedback loop acts as compensatory mechanism that aims to restore homeostasis following initial perturbation of a KE, the feedback loop will directly shape the response-response relationship between the KERs. Given interest in formally identifying these positive or negative feedback, it is recommended that a graphical annotation (page 44) indicating a positive or negative feedback loop is involved in a particular upstream to downstream KE transition (KER) be added to the graphical representation, and that details be provided in this subsection of the KER description (see pages 44-45 of the User Handbook).  More help

Not identified.

Domain of Applicability

As for the KEs, there is also a free-text section of the KER description that the developer can use to explain his/her rationale for the structured terms selected with regard to taxonomic, life stage, or sex applicability, or provide a more generalizable or nuanced description of the applicability domain than may be feasible using standardized terms. More help

The domain of applicability applies to eukaryotic cells and multi-cellular organisms such as mice and humans.


List of the literature that was cited for this KER description using the appropriate format. Ideally, the list of references should conform, to the extent possible, with the OECD Style Guide (OECD, 2015). More help

Abe, Y. et al. (2018), "Dose–response curves for analyzing of dicentric chromosomes and chromosome translocations following doses of 1000 mGy or less, based on irradiated peripheral blood samples from fi ve healthy individuals.", J. Radiat. Res., 59(1):35–42. doi:10.1093/jrr/rrx052.

Adewoye, A.B. et al. (2015),  "Mutation induction in the mammalian germline.", Nature Comm. 6:(6684), doi:10.1038/ncomms7684.

Arlt, M.F. et al. (2014), "Copy number variants are produced in response to low-dose ionizing radiation in cultured cells", Envrion. and Mol. Mutagen, 55(2):103–113. doi:10.1002/em.21840.

Balajee, A.S. et al. (2014), "Multicolour FISH analysis of ionising radiation induced micronucleus formation in human lymphocytes.", Mutagenesis, 29(6):447–455. doi:10.1093/mutage/geu041.

Barquinero JF, Stephan G and Schmid E. 2004. Effect of americium-241 alpha-particles on the dose-response of chromosome aberations in human lymphocytes analysed by fluorescence in situ hybridization. Int J Radiat Biol. 80(2):155-164.

Basheerudeen, S.S. et al. (2017), "Entrance surface dose and induced DNA damage in blood lymphocytes of patients exposed to low-dose and low-dose-rate X-irradiation during diagnostic and therapeutic interventional radiology procedures.", Mutat Res Gen Tox En. 818(April):1–6., doi:10.1016/j.mrgentox.2017.04.001.

Bender, M.A. et al. (1988), "Current status of cytogenetic procedures to detect and quantify previous exposures to radiation.", Mutat Res Genet Toxicol. 196(2):103–159. doi:10.1016/0165-1110(88)90017-6.

Bergs, J.W. et al. (2016), "Dynamics of chromosomal aberrations, induction of apoptosis, BRCA2 degradation and sensitization to radiation by hyperthermia.", Int. J. Mol. Med., 38(1):243–250. doi:10.3892/ijmm.2016.2611.

Bilbao A, Prosser JS, Edwards AA, Moody JC, Lloyd DC. 1989. The Induction of Micronuclei in Human Lymphocytes by in vitro Irradiation with Alpha Particles from Plutonium-239. Int J Radiat Biol. 56(3):287-292.

Bonassi, S. et al. (2008), "Chromosomal aberration frequency in lymphocytes predicts the risk of cancer: results from a pooled cohort study of 22,358 subjects in 11 countries.", Carcinogenesis, 29(6):1178–1183. doi:10.1093/carcin/bgn075.

Brooks AL. 1975. Chromosome damage in liver cells from low dose rate alpha, beta, and gamma irradiation: derivation of RBE. Sci. 190(4219):1090-1092.

Cheki, M. et al. (2016), "The radioprotective effect of metformin against cytotoxicity and genotoxicity induced by ionizing radiation in cultured human blood lymphocytes.", Mutat Res - Genet Toxicol Environ Mutagen. 809:24–32. doi:10.1016/j.mrgentox.2016.09.001.

Christensen, D.M. (2014), "Management of Ionizing Radiation Injuries and Illnesses, Part 3: Radiobiology and Health Effects of Ionizing Radiation.", J. Am. Osteopath Assoc., 114(7):556–565. doi:10.7556/jaoa.2014.109.

Cornforth MN, Bailey SM, Goodwin EH. 2002. Dose Responses for Chromsome Aberrations Produced in Noncycling Primary Human Fibroblasts by Alpha Particles, and by Gamma Rays Delivered at Sublimating Low Dose Rates. Radiat Res. 158:43-53.

Curwen GB, Tawn EJ, Cadwell KK, Guyatt L, Thompson J, Hill MA. 2012. mFISH Analysis of Chromsome Aberrations Induced In Vitro by Alpha-Particle Radiation: Examination of Dose-Response Relationships. Radiat Res. 178:414-424.

Day, T.K. et al. (2007), "Adaptive Response for Chromosomal Inversions in pKZ1 Mouse Prostate Induced by Low Doses of X Radiation Delivered after a High Dose.", Radiat Res. 167(6):682–692. doi:10.1667/rr0764.1.

Durante M, Grossi GF, Napolitano M, Pugliese M, Gialanella G. 1992. Chromsome damage induced by high-LET alpha-particles in plateau-phase C3H 10T1/2 cells. Int J Radiat Biol. 62(5):571-580.

Edwards AA, Purrott RJ, Prosser JS, Lloyd DC. 1980. The induction of chromosome aberrations in human lymphocytes by alpha-radiation. Int J Radiat Biol. 38(1):83-91.

duFrain RJ, Littlefield G, Joiner EE, Frome EL. 1979. Human Cytogenetic Dosimetry: A Dose-Response Relationship for Alpha Particle Radiation from 241Am. Health Phys. 37:279-289.

Franken NAP, Hovingh S, Cate RT, Krawczyk P, Stap J, Hoebe R, Aten J, Barendsen GW. 2012. Relative biological effectiveness of high linear energy transfer alpha-particles for the induction of DNA-double-strand breaks, chromosome aberrations and reproductive cell death in SW-1573 lung tumour cells. Oncol reports. 27:769-774.

George, A., R. Dey & V.B. Dqhumhh (2014), "Nuclear Anomalies, Chromosomal Aberrations and Proliferation Rates in Cultured Lymphocytes of Head and Neck Cancer Patients.", Asian Pacific journal of cancer prevention. 15(3):1119-1123. doi:10.7314/APJCP.2014.15.3.1119.

George, K.A. et al. (2009), "Dose Response of γ Rays and Iron Nuclei for Induction of Chromosomal Aberrations in Normal and Repair-Deficient Cell Lines Dose Response of c Rays and Iron Nuclei for Induction of Chromosomal Aberrations in Normal and Repair-Deficient Cell Lines.", Radiat. Res., 171(6):752–763.doi: 10.1667/RR1680.1.

Guerrero-Carbajal, C., A.A. Edwards & D.C. Lloyd (2003), "Induction of chromosome aberration in human lymphocytes and its dependence on X ray energy. Radiat Prot Dosimetry.", Radiat. Prot. Dosimetry 106(2):131–135. doi:10.1093/oxfordjournals.rpd.a006342.

Hada, M. & A.G. Georgakilas (2008), "Formation of Clustered DNA Damage after High-LET Irradiation: A Review.", J. Radiat. Res., 49(3):203–210. doi:10.1269/jrr.07123.

Hagmar, L. et al. (2004), "Impact of Types of Lymphocyte Chromosomal Aberrations on Human Cancer Risk : Results from Nordic and Italian Cohorts.", Cancer Res., 64(6):2258–2263. doi: 10.1158/0008-5472.CAN-03-3360.

Hamza VZ and Mohankumar MN. 2009. Cytogenetic damage in human blood lymphocytes exposed in vitro to radon. Mutat Res. 661(1-2):1-9.

Han. L. et al. (2014), "Cytogenetic analysis of peripheral blood lymphocytes, many years after exposure of workers to low-dose ionizing radiation.", Mutat. Res. Genet. Toxicol. Environ. Mutagen. 1(771):1–5, doi: 10.1016/j.mrgentox.2014.06.003

Hunter, N. & C.R. Muirhead (2009), "Review of relative biological effectiveness dependence on linear energy transfer for low-LET radiations Review of relative biological effectiveness dependence.", J. Radiol. Prot. 29(1):5-21, doi:10.1088/0952-4746/29/1/R01.

Jang, M. et al. (2019), "Dose Estimation Curves Following In Vitro X-ray Irradiation Using Blood From Four Healthy Korean Individuals.", Ann. Lab. Med. 39(1):91–95, doi: 10.3343/alm.2019.39.1.91.

Karthik K, Rajan V, Pandey BN, Sivasubramanian K, Paul SFD, Venkatachalam P, 2019. Direct and bystander effects in human blood lymphocytes exposed to 241Am alpha particles and the relative biological effectiveness using chromosomal aberration and micronucleus assay. Int J Radiat Biol. 95(6):725-736.

Li, W. A. Lee & P.K. Gregersen (2009), "Copy-number-variation and copy-number-alteration region detection by cumulative plots.", BMC Bioinformatics, 10(Suppl. 1):S67, doi:10.1186/1471-2105-10-S1-S67.

Lorat. Y. et al. (2015), "Nanoscale analysis of clustered DNA damage after high-LET irradiation by quantitative electron microscopy – The heavy burden to repair.", DNA Repair (Amst). 28:93–106. doi:10.1016/j.dnarep.2015.01.007.

Loucas BD, Durante M, Bailey SM, Cornforth MN. 2013. Chromosome Damage in Human Cells by Gamma Rays, Alpha Particles and Heavy Ions: Track Interactions in Basic Dose-Response Relationships. Radiat Res. 179(1):9-20.

Maffei, F. et al. (2004), "Spectrum of chromosomal aberrations in peripheral lymphocytes of hospital workers occupationally exposed to low doses of ionizing radiation.", Mutat Res., 547(1-2):91–99. doi:10.1016/j.mrfmmm.2003.12.003.

McMahon, S.J. et al. (2016), "Mechanistic Modelling of DNA Repair and Cellular Survival Following Radiation-Induced DNA Damage.", Nat. Publ. Gr.(April):1–14. doi:10.1038/srep33290.

Meenakshi, C. & M.N. Mohankumar (2013), "Synergistic effect of radon in blood cells of smokers - An in vitro study.", Mutat. Res., 757(1):79–82. doi: 10.1016/j.mrgentox.2013.06.018.

Meenakshi, C., K. Sivasubramanian & B. Venkatraman (2017), "Nucleoplasmic bridges as a biomarker of DNA damage exposed to radon.", Mutat Res - Genet Toxicol Environ Mutagen. 814:22–28. doi:10.1016/j.mrgentox.2016.12.004.

Mestres M, Caballin MR, Schmid E, Stephan E, Stephan G, Sachs R, Barrios L, Barquinero JF. 2004. Analysis of alpha-particle induced chromosome aberrations in human lymphocytes, using pan-centromeric and pan-telomeric probes. 80(10):737-744.

Mill AJ, Wells J, Hall SC, Butler A. 1996. Micronucleus Induction in Human Lymphocytes: Comparative Effects of X Rays, Alpha Particles, Beta Particles and Neutrons and Implications for Biological Dosimetry. Radiat Res. 145:575-585.

Moquet JE, Fernandex JL, Edwards AA, Lloyd DC. 2001. Lymphocytes Chromsomal Aberrations and Their Complexity Induced In Vitro by Plutonium-239 Alpha-Particles and Detected by FISH. Cell Mol Biol. 47(3):549-556.

Morishita, M. et al. (2016), "Chromothripsis-like chromosomal rearrangements induced by ionizing radiation using proton microbeam irradiation system.", Oncotarget, 7(9):10182-10192, doi:10.18632/oncotarget.7186.

Nagasawa H, Little JB, Inkret WC, Carpenter S, Thompson K, Raju MR, Chen DJ, Strniste GF. 1990a. Cytogenetic effects of extremely low doses of plutonium-238 alpha-particle irradiation in CHO K-1 cells. Mutat Res. 244:233-238.

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