Clustered Damage Research Articles

Migration and clustering of early-stage irradiation damage in vanadium

Migration and clustering of early-stage irradiation damage in vanadium

Fenebrutinib, a Bruton’s tyrosine kinase inhibitor, blocks distinct human microglial signaling pathways

BackgroundBruton’s tyrosine kinase (BTK) is an intracellular signaling enzyme that regulates B-lymphocyte and myeloid cell functions. Due to its involvement in both innate and adaptive immune compartments, BTK inhibitors have emerged as a therapeutic option in autoimmune disorders such as multiple sclerosis (MS). Brain-penetrant, small-molecule BTK inhibitors may also address compartmentalized neuroinflammation, which is proposed to underlie MS disease progression. BTK is expressed by microglia, which are the resident innate immune cells of the brain; however, the precise roles of microglial BTK and impact of BTK inhibitors on microglial functions are still being elucidated. Research on the effects of BTK inhibitors has been limited to rodent disease models. This is the first study reporting effects in human microglia.MethodsHere we characterize the pharmacological and functional properties of fenebrutinib, a potent, highly selective, noncovalent, reversible, brain-penetrant BTK inhibitor, in human microglia and complex human brain cell systems, including brain organoids.ResultsWe find that fenebrutinib blocks the deleterious effects of microglial Fc gamma receptor (FcγR) activation, including cytokine and chemokine release, microglial clustering and neurite damage in diverse human brain cell systems. Gene expression analyses identified pathways linked to inflammation, matrix metalloproteinase production and cholesterol metabolism that were modulated by fenebrutinib treatment. In contrast, fenebrutinib had no significant impact on human microglial pathways linked to Toll-like receptor 4 (TLR4) and NACHT, LRR and PYD domains-containing protein 3 (NLRP3) signaling or myelin phagocytosis.ConclusionsOur study enhances the understanding of BTK functions in human microglial signaling that are relevant to MS pathogenesis and suggests that fenebrutinib could attenuate detrimental microglial activity associated with FcγR activation in people with MS.

Effect of Ultrahigh Dose Rate on Biomolecular Radiation Damage.

Dose rate is one of the important parameters in radiation-induced biomolecular damage. The effects of dose rate have been known to modify radiation toxicity in biological systems. The rate and extent of sublethal DNA damage (e.g., base damage and single-strand breaks) repair and those of cell proliferation have been manifested by dose rate. However, the recent preclinical application of ultrahigh dose rate [(UHDR) ca. 40 Gy/s and higher] radiation modalities have been shown to lower the type and extent of radiation damage to biological systems. At these UHDR, radiation-induced physicochemical and chemical processes are expected to differ from those observed after irradiation at conventional dose rates (CONV). It is unclear whether these UHDR conditions can affect the quality (type) and quantity (extent) of biomolecular damage such as DNA lesions. Here, we comparatively study the influence of indirect effects of CONV and UHDR on the formation of DNA strand breaks and clustered damage including densely accumulated lesions in an aerated and an anoxic dilute aqueous solution of a plasmid DNA model under low and high hydroxyl radical (•OH) scavenging conditions. Aqueous solutions of purified supercoiled plasmid DNA (pUC19) were prepared in either air- or nitrogen-saturated conditions, with Tris buffer added as the radiation-produced •OH scavenger at low and high scavenging capacities. These DNA samples were irradiated using kV X-ray systems at CONV (0.1 Gy/s) and high dose rate (HDR, 25 Gy/s) as well as UHDR (55 and 125 Gy/s) under different scavenging and environmental conditions. DNA lesions including strand breaks and clustered damage including densely accumulated lesions were quantified by gel electrophoresis and the yields of these lesions were calculated from the dose-response curve. Non-DSB clustered damage including densely accumulated lesions were evaluated by treating DNAs using bacterial endonuclease enzymes (Fpg and Nth) prior to gel electrophoresis. UHDR of 55 and 125 Gy/s induced lower amounts of both isolated strand breaks and clustered DNA damage including densely accumulated lesions at doses >40 Gy in the presence of oxygen, compared to the abundance of these lesions induced by 0.1 and 25 Gy/s irradiation under the same dose conditions. Overall, the strand break and clustered damage including densely accumulated lesions yields decreased by factors of 1.3-3.5 after UHDR. We did not observe these differences either via •OH scavenging or by removing oxygen from the solution. In addition, our results point out that the inter-track recombination reactions did not contribute to the observed dose-rate effects on DNA damage. The effects of dose rate on DNA damage are highly dependent on the total dose, as expected, but also on the •OH scavenging capacity that is employed in the aqueous DNA solutions. These important variables may be relevant in biological systems as well. On a practical level, our in vitro plasmid DNA model, which permits to precisely vary the scavenging capacity and gassing conditions (air saturated vs. N2 saturated) can help to differentiate dose-rate effects on biomolecular damage. Our results indicate that the radical-radical reactions are important in understanding the dose-rate effect on DNA damage.

Experimental study on acoustic emission damage in precast reinforced concrete interior joints containing disc springs

To address the inferior performance of precast reinforced concrete beam-column joints compared to cast-in-place joints during earthquakes, this study designed a precast concrete frame beam-column interior joint incorporating disc springs. The disc springs, installed based on grouted sleeve connections, aimed to enhance structural ductility and mitigate seismic forces on the joints. Five joints, including one cast-in-place joint, two ordinary precast joints, and two precast joints with disc springs, were tested quasi-statically and monitored using acoustic emission technology. The precast joints had axial compression ratios of 0.2 and 0.4. Parameters such as energy, count, and b-value from acoustic emission monitoring were analyzed. The Gaussian mixture model was employed for the clustering analysis of RA-AF parameters, and a damage model was developed to evaluate performance differences among the joints in the quasi-static tests. The results indicate that precast joints with the same axial compression ratio can achieve performance similar to cast-in-place joints, with more rapid damage development at higher axial compression ratios. Installing disc springs decelerates damage progression in the later stages of loading, maintaining joint integrity for a certain period even after reaching maximum load, thereby demonstrating improved ductility. At higher axial compression ratios, the b-value curve of joints with disc springs more closely resembles that of ordinary joints. Disc springs' positive effect is more pronounced in clustering analysis and damage models, such as their lower proportion of shear fractures.

Differential FeS cluster photodamage plays a critical role in regulating excess electron flow through photosystem I.

The photosynthetic electron flux from photosystem I (PSI) is mainly directed to NADP+ and CO2 fixation, but a fraction is always shared between alternative and cyclic electron transport. Although the electron transfer from P700 to ferredoxin, via phylloquinone and the FeSX, FeSB and FeSA clusters, is well characterized, the regulatory role of these redox intermediates in the delivery of electrons from PSI to NADP+, alternative and cyclic electron transport under environmental stress remains elusive. Here we provide evidence for sequential damage to PSI FeS clusters under high light and subsequent slow recovery under low light in Arabidopsis thaliana. Wild-type plants showed 10-35% photodamage to their FeSA/B clusters with increasing high-light duration, without much effect on P700 oxidation capacity, FeSX function or CO2 fixation rate, and without additional oxygen consumption (O2 photoreduction). Parallel FeSA/B cluster damage in the pgr5 mutant was more pronounced at 50-85%, probably due to weak photosynthetic control and low non-photochemical quenching. Such severe electron pressure on PSI was also shown to damage the FeSX clusters, with a concomitant decrease in P700 oxidation capacity and a decrease in thylakoid-bound ferredoxin in the pgr5 mutant. The results from wild-type and pgr5 plants reveal controlled damage of PSI FeS clusters under high light. In wild-type plants, this favours electron transport to linear over alternative pathways by intact PSI centres, thereby preventing reactive oxygen species production and probably promoting harmless charge recombination between P700+ and FeSX- as long as the majority of FeSA/B clusters remain functional.

The Hole Truth: Why Do Bumble Bees Rob Flowers More Than Once?

Primary nectar-robbers feed through holes they make in flowers, often bypassing the plant's reproductive organs in the process. In many robbed plants, multiple holes are made in a single flower. Why a flower should be robbed repeatedly is difficult to understand: a hole signals that a nectar forager has already fed, which would seem likely to predict low rewards. We tested three explanations for this pattern in Corydalis caseana (Fumariaceae), a bumble bee pollinated and robbed plant: (1) multiple holes appear only after all flowers have been robbed once; (2) individual foragers make multiple holes during single visits; and (3) it is more profitable for bees to rob older flowers, even if they have already been robbed. We tested these hypotheses from 2014 to 2016 in a Colorado, USA population using data on robbing rates over time, floral longevity, nectar accumulation in visited and unvisited flowers, and the accumulation of robbing holes across the life of flowers. Multiple holes were already appearing when two-thirds of flowers still lacked a single hole, allowing us to reject the first hypothesis. The second hypothesis cannot offer a full explanation for multiple robbing holes because 35% of additional holes appeared in flowers one or more days after the first hole was made. Repeated sampling of bagged and exposed inflorescences revealed that flowers filled at a constant rate and refilled completely after being drained. Consequently, young flowers are of consistently low value to foragers compared to older flowers even if they had previously been robbed, consistent with the third hypothesis. While further studies are needed, these results offer a simple explanation for the paradoxical clustering of nectar-robbing damage in this and possibly other plant species.

Damage identification of plain-woven composites at T > Tg using AE: Damage clustering and initiation detection

In this work, the damage modes and their initiation detections of plain-woven composites under tensile and compressive loads at T > Tg are investigated by conducting a comprehensive analysis of AE signals, including the feature selection, algorithm comparison and clustering validity. According to a newly proposed Pearson correlation coefficient cumulative criterion, the PF and PA are the most representative features of AE signals. A systematic comparison of K-Means, GMM and Hierarchical model, reveals that the Hierarchical model is the most suitable clustering algorithm for plain-woven composites at T > Tg. The cluster validity indexes combined with microscopic observations identify matrix cracking, interface debonding and fiber breakage as the three dominant damage modes, with PF ranges of [0–200 kHz], [200–350 kHz] and [350–600 kHz], respectively, and independent of different loading conditions. Three damage initiation criteria, sentry function, b-value and cumulative AE counts, are compared and the sentry function is determined to be optimal. The damage initiations of matrix cracking, interface debonding and fiber breakage within plain-woven composites at T > Tg can be effectively detected by AE.

Study of Neutron-, Proton-, and Gamma-Irradiated Silicon Detectors Using the Two-Photon Absorption-Transient Current Technique.

The Two-Photon Absorption-Transient Current Technique (TPA-TCT) is a device characterisation technique that enables three-dimensional spatial resolution. Laser light in the quadratic absorption regime is employed to generate excess charge carriers only in a small volume around the focal spot. The drift of the excess charge carriers is studied to obtain information about the device under test. Neutron-, proton-, and gamma-irradiated p-type pad silicon detectors up to equivalent fluences of about 7 × 1015 neq/cm2 and a dose of 186 Mrad are investigated to study irradiation-induced effects on the TPA-TCT. Neutron and proton irradiation lead to additional linear absorption, which does not occur in gamma-irradiated detectors. The additional absorption is related to cluster damage, and the absorption scales according to the non-ionising energy loss. The influence of irradiation on the two-photon absorption coefficient is investigated, as well as potential laser beam depletion by the irradiation-induced linear absorption. Further, the electric field in neutron- and proton-irradiated pad detectors at an equivalent fluence of about 7 × 1015 neq/cm2 is investigated, where the space charge of the proton-irradiated devices appears inverted compared to the neutron-irradiated device.

The role of DNA polymerase I in tolerating single-strand breaks generated at clustered DNA damage in Escherichia coli

Clustered DNA damage, when multiple lesions are generated in close proximity, has various biological consequences, including cell death, chromosome aberrations, and mutations. It is generally perceived as a hallmark of ionizing radiation. The enhanced mutagenic potential of lesions within a cluster has been suggested to result, at least in part, from the selection of the strand with the mutagenic lesion as the preferred template strand, and that this process is relevant to the tolerance of persistent single-strand breaks generated during an attempted repair. Using a plasmid-based assay in Escherichia coli, we examined how the strand bias is affected in mutant strains deficient in different DNA polymerase I activities. Our study revealed that the strand-displacement and 5′-flap endonuclease activities are required for this process, while 3′-to-5′ exonuclease activity is not. We also found the strand template that the mutagenic lesion was located on, whether lagging or leading, had no effect on this strand bias. Our results imply that an unknown pathway operates to repair/tolerate the single-strand break generated at a bi-stranded clustered damage site, and that there exist different backup pathways, depending on which DNA polymerase I activity is compromised.

A damage-related adaptive self-consistent clustering analysis method with localized refinement capability for the damage problem of 3D woven composites

In this work, a Damage-related Adaptive Self-Consistent Clustering Analysis (DASCA) method is developed to achieve higher solving accuracy for 3D damage problems than Self-Consistent Clustering Analysis (SCA) method, which is applied to investigate the mesoscale damage behavior of 3D woven composites (3DWC). The developed clustering adaptivity framework is based on the characteristics of the damage problem, which consists of five fundamental stages: evaluation of the adaptivity conditions, selection criterion of potential damage clusters, online adaptive clustering analysis, update of the cluster database and adaptive rewind of the analysis process. In the second stage, the clusters with the highest potential to enter the damage state are identified and marked as adaptivity target clusters. In the solving process, the distribution of clusters can achieve problem-dependent dynamic adjustments, ensuring that clusters are concentrated on the regions of interest. Though the numerical examples of 3DWC, the DASCA solutions, using fewer clusters and less computational cost, exhibit higher prediction accuracy for macroscopic mechanical performance, first damage initiation moments and damage evolution process than the SCA solutions.

Ensemble Feature Selection for Clustering Damage Modes in Carbon Fiber‐Reinforced Polymer Sandwich Composites Using Acoustic Emission

Acoustic emission (AE) serves as a noninvasive technique for real‐time structural health monitoring, capturing the stress waves produced by the formation and growth of cracks within a material. This study presents a novel ensemble feature selection methodology to rank features highly relevant with damage modes in AE signals gathered from edgewise compression tests on honeycomb‐core carbon fiber‐reinforced polymer. Two distinct features, amplitude and peak frequency, are selected for labeling the AE signals. An ensemble‐supervised feature selection method ranks feature importance according to these labels. Using the ranking list, unsupervised clustering models are then applied to identify damage modes. The comparative results reveal a robust correlation between the damage modes and the features of counts and energy when amplitude is selected. Similarly, when peak frequency is chosen, a significant association is observed between the damage modes and the features of partial powers 1 and 2. These findings demonstrate that, in addition to the commonly used features, other features, such as partial powers, exhibit a correlation with damage modes.

Clustered DNA Damage and its Complexity: Tracking the History.

The concept of radiation-induced clustered damage in DNA has grown over the past several decades to become a topic of considerable interest across the scientific disciplines involved in studies of the biological effects of ionizing radiation. This paper, prepared for the 70th anniversary issue of Radiation Research, traces historical development of the three main threads of physics, chemistry, and biochemical/cellular responses that led to the hypothesis and demonstration that a key component of the biological effectiveness of ionizing radiation is its characteristic of producing clustered DNA damage of varying complexities. The physics thread has roots that started as early as the 1920s, grew to identify critical nanometre-scale clusterings of ionizations relevant to biological effectiveness, and then, by the turn of the century, had produced an extensive array of quantitative predictions on the complexity of clustered DNA damage from different radiations. Monte Carlo track structure simulation techniques played a key role through these developments, and they are now incorporated into many recent and ongoing studies modelling the effects of radiation. The chemistry thread was seeded by water-radiolysis descriptions of events in water as radical-containing "spurs," demonstration of the important role of the hydroxyl radical in radiation-inactivation of cells and the difficulty of protection by radical scavengers. This led to the concept and description of locally multiply damaged sites (LMDS) for DNA double-strand breaks and other combinations of DNA base damage and strand breakage that could arise from a spur overlapping, or created in very close proximity to, the DNA. In these ways, both the physics and the chemistry threads, largely in parallel, put out the challenge to the experimental research community to verify these predictions of clustered DNA damage from ionizing radiations and to investigate their relevance to DNA repair and subsequent cellular effects. The third thread, biochemical and cell-based research, responded strongly to the challenge by demonstrating the existence and biological importance of clustered DNA damage. Investigations have included repair of a wide variety of defined constructs of clustered damage, evaluation of mutagenic consequences, identification of clustered base-damage within irradiated cells, and identification of co-localization of repair complexes indicative of complex clustered damage after high-LET irradiation, as well as extensive studies of the repair pathways involved in repair of simple double-strand breaks. There remains, however, a great deal more to be learned because of the diversity of clustered DNA damage and of the biological responses.

Clusters of resilience and vulnerability: executive functioning, coping and mental distress in patients with diffuse low-grade glioma

PurposeDiffuse low-grade gliomas (dLGG) often have a frontal location, which may negatively affect patients’ executive functions (EF). Being diagnosed with dLGG and having to undergo intensive treatment can be emotionally stressful. The ability to cope with this stress in an adaptive, active and flexible way may be hampered by impaired EF. Consequently, patients may suffer from increased mental distress. The aim of the present study was to explore profiles of EF, coping and mental distress and identify characteristics of each profile.Methods151 patients with dLGG were included. Latent profile analysis (LPA) was used to explore profiles. Additional demographical, tumor and radiological characteristics were included.ResultsFour clusters were found: 1) overall good functioning (25% of patients); 2) poor executive functioning, good psychosocial functioning (32%); 3) good executive functioning, poor psychosocial functioning (18%) and; 4) overall poor functioning (25%). Characteristics of the different clusters were lower educational level and more (micro)vascular brain damage (cluster 2), a younger age (cluster 3), and a larger tumor volume (cluster 4). EF was not a distinctive factor for coping, nor was it for mental distress. Maladaptive coping, however, did distinguish clusters with higher mental distress (cluster 3 and 4) from clusters with lower levels of mental distress (cluster 1 and 2).ConclusionFour distinctive clusters with different levels of functioning and characteristics were identified. EF impairments did not hinder the use of active coping strategies. Moreover, maladaptive coping, but not EF impairment, was related to increased mental distress in patients with dLGG.

Machine-learning clustering analysis identifies novel phenogroups in patients with ST-elevation acute myocardial infarction

BackgroundMachine learning clustering of patients with ST-elevation acute myocardial infarction (STEMI) may provide important insights into their risk profile, management and prognosis. MethodsAll adult discharges for STEMI in the National Inpatient Sample (October 2015 to December 2019) were included, excluding patients with prior myocardial infarction. Machine-learning clustering analysis was used to define clusters based on 21 clinical attributes of interest. Main outcomes of the study were cluster-based comparison of risk profile, in-hospital clinical outcomes and utilization of invasive management. Binomial hierarchical multivariable logistic regression with adjusted odds ratios (aOR) and 95% confidence intervals (95% CI) was used to detect the between-cluster differences. ResultsOut of overall 470,960 STEMI cases, the machine-learning analysis revealed 4 different clusters with 205,640 (cluster 0: ‘behavioural risk cluster’), 146,400 (cluster 1: ‘least comorbidity cluster’), 45,100 (cluster 2: ‘diabetes with end-organ damage cluster’) and 73,820 (cluster 3: ‘cardiometabolic cluster’) cases. Attributes with the highest importance for clustering were hypertension and diabetes. After multivariable adjustment, patients from ‘diabetes with end-organ damage cluster’ exhibited the worst mortality, MACCE and ischemic stroke (p < 0.001 for all), as well as the lowest utilization of invasive management (p < 0.001 for all), in comparison to other clusters. Patients from ‘behavioural risk cluster’ exhibited the best in-hospital prognosis and the highest utilization of invasive management, compared to other clusters (p < 0.001 for all). ConclusionsMachine learning driven clustering of inpatients with STEMI reveals important population subgroups with distinct prevalence, risk profile, prognosis and management. Data driven approaches may identify high risk phenogroups and warrants further study.

How a Single 5 eV Electron Can Induce Double-Strand Breaks in DNA: A Time-Dependent Density Functional Theory Study.

Low-energy (<20 eV) electrons (LEEs) can resonantly interact with DNA to form transient anions (TAs) of fundamental units, inducing single-strand breaks (SSBs), and cluster damage, such as double-strand breaks (DSBs). Shape resonances, which arise from electron capture in a previously unfilled orbital, can induce only a SSB, whereas a single core-excited resonance (i.e., two electrons in excited orbitals of the field of a hole) has been shown experimentally to cause cluster lesions. Herein, we show from time-dependent density functional theory (TDDFT) that a core-excited resonance can produce a DSB, i.e., a single 5 eV electron can induce two close lesions in DNA. We considered the nucleotide with the G-C base pair (ds[5'-G-3']) as a model for electron localization in the DNA double helix and calculated the potential energy surfaces (PESs) of excited states of the ground-state TA of ds[5'-G-3'], which correspond to shape and core-excited resonances. The calculations show that shape TAs start at ca. 1 eV, while core-excited TAs occur only above 4 eV. The energy profile of each excited state and the corresponding PES are obtained by simultaneously stretching both C5'-O5' bonds of ds[5'-G-3']. From the nature of the PES, we find two dissociative (σ*) states localized on the PO4 groups at the C5' sites of ds[5'-G-3']. The first σ* state at 1 eV is due to a shape resonance, while the second σ* state is induced by a core-excited resonance at 5.4 eV. As the bond of the latter state stretches and arrives close to the dissociation limit, the added electron on C transfers to C5' phosphate, thus demonstrating the possibility of producing a DSB with only one electron of ca. 5 eV.

‘Nowhere and no one is safe’: spatial analysis of damage to critical civilian infrastructure in the Gaza Strip during the first phase of the Israeli military campaign, 7 October to 22 November 2023

BackgroundSince the Hamas attacks in Israel on 7 October 2023, the Israeli military has launched an assault in the Gaza Strip, which included over 12,000 targets struck and over 25,000 tons of incendiary munitions used by 2 November 2023. The objectives of this study include: (1) the descriptive and inferential spatial analysis of damage to critical civilian infrastructure (health, education, and water facilities) across the Gaza Strip during the first phase of the military campaign, defined as 7 October to 22 November 2023 and (2) the analysis of damage clustering around critical civilian infrastructure to explore broader questions about Israel’s adherence to International Humanitarian Law (IHL).MethodsWe applied multi-temporal coherent change detection on Copernicus Sentinel 1-A Synthetic Aperture Radar (SAR) imagery to detect signals indicative of damage to the built environment through 22 November 2023. Specific locations of health, education, and water facilities were delineated using open-source building footprint and cross-checked with geocoded data from OCHA, OpenStreetMap, and Humanitarian OpenStreetMap Team. We then assessed the retrieval of damage at and with close proximity to sites of health, education, and water infrastructure in addition to designated evacuation corridors and civilian protection zones. The Global Moran’s I autocorrelation inference statistic was used to determine whether health, education, and water facility infrastructure damage was spatially random or clustered.ResultsDuring the period under investigation, in the entire Gaza Strip, 60.8% (n = 59) of health, 68.2% (n = 324) of education, and 42.1% (n = 64) of water facilities sustained infrastructure damage. Furthermore, 35.1% (n = 34) of health, 40.2% (n = 191) of education, and 36.8% (n = 56) of water facilities were functionally destroyed. Applying the Global Moran’s I spatial inference statistic to facilities demonstrated a high degree of damage clustering for all three types of critical civilian infrastructure, with Z-scores indicating < 1% likelihood of cluster damage occurring by random chance.ConclusionSpatial statistical analysis suggests widespread damage to critical civilian infrastructure that should have been provided protection under IHL. These findings raise serious allegations about the violation of IHL, especially in light of Israeli officials’ statements explicitly inciting violence and displacement and multiple widely reported acts of collective punishment.

Carbon Ion Irradiation Activates Anti-Cancer Immunity.

Carbon ion beams have the unique property of higher linear energy transfer, which causes clustered damage of DNA, impacting the cell repair system. This sometimes triggers apoptosis and the release in the cytoplasm of damaged DNA, leading to type I interferon (IFN) secretion via the activation of the cyclic GMP-AMP synthase-stimulator of interferon genes pathway. Dendritic cells phagocytize dead cancer cells and damaged DNA derived from injured cancer cells, which together activate dendritic cells to present cancer-derived antigens to antigen-specific T cells in the lymph nodes. Thus, carbon ion radiation therapy (CIRT) activates anti-cancer immunity. However, cancer is protected by the tumor microenvironment (TME), which consists of pro-cancerous immune cells, such as regulatory T cells, myeloid-derived suppressor cells, and tumor-associated macrophages. The TME is too robust to be destroyed by the CIRT-mediated anti-cancer immunity. Various modalities targeting regulatory T cells, myeloid-derived suppressor cells, and tumor-associated macrophages have been developed. Preclinical studies have shown that CIRT-mediated anti-cancer immunity exerts its effects in the presence of these modalities. In this review article, we provide an overview of CIRT-mediated anti-cancer immunity, with a particular focus on recently identified means of targeting the TME.

DNA break clustering as a predictor of cell death across various radiation qualities: influence of cell size, cell asymmetry, and beam orientation

Abstract Cosmic radiation, composed of high charge and energy (HZE) particles, causes cellular DNA damage that can result in cell death or mutation that can evolve into cancer. In this work, a cell death model is applied to several cell lines exposed to HZE ions spanning a broad range of linear energy transfer (LET) values. We hypothesize that chromatin movement leads to the clustering of multiple double strand breaks (DSB) within one radiation-induced foci (RIF). The survival probability of a cell population is determined by averaging the survival probabilities of individual cells, which is function of the number of pairwise DSB interactions within RIF. The simulation code RITCARD was used to compute DSB. Two clustering approaches were applied to determine the number of RIF per cell. RITCARD outputs were combined with experimental data from four normal human cell lines to derive the model parameters and expand its predictions in response to ions with LET ranging from ~0.2 keV/μm to ~3000 keV/μm. Spherical and ellipsoidal nuclear shapes and two ion beam orientations were modeled to assess the impact of geometrical properties on cell death. The calculated average number of RIF per cell reproduces the saturation trend for high doses and high-LET values that is usually experimentally observed. The cell survival model generates the recognizable bell shape of LET dependence for the relative biological effectiveness (RBE). At low LET, smaller nuclei have lower survival due to increased DNA density and DSB clustering. At high LET, nuclei with a smaller irradiation area—either because of a smaller size or a change in beam orientation—have a higher survival rate due to a change in the distribution of DSB/RIF per cell. If confirmed experimentally, the geometric characteristics of cells would become a significant factor in predicting radiation-induced biological effects. Insight Box: High-charge and energy (HZE) ions are characterized by dense linear energy transfer (LET) that induce unique spatial distributions of DNA damage in cell nuclei that result in a greater biological effect than sparsely ionizing radiation like X-rays. HZE ions are a prominent component of galactic cosmic ray exposure during human spaceflight and specific ions are being used for radiotherapy. Here, we model DNA damage clustering at sub-micrometer scale to predict cell survival. The model is in good agreement with experimental data for a broad range of LET. Notably, the model indicates that nuclear geometry and ion beam orientation affect DNA damage clustering, which reveals their possible role in mediating cell radiosensitivity.

The Effects of Particle LET and Fluence on the Complexity and Frequency of Clustered DNA Damage.

Clustered DNA-lesions are predominantly induced by ionizing radiation, particularly by high-LET particles, and considered as lethal damage. Quantification of this specific type of damage as a function of radiation parameters such as LET, dose rate, dose, and particle type can be informative for the prediction of biological outcome in radiobiological studies. This study investigated the induction and complexity of clustered DNA damage for three different types of particles at an LET range of 0.5-250 keV/μm. Nanometric volumes (36.0 nm3) of 15 base-pair DNA with its hydration shell was modeled. Electron, proton, and alpha particles at various energies were simulated to irradiate the nanometric volumes. The number of ionization events, low-energy electron spectra, and chemical yields for the formation of °OH, H°, , and H2O2 were calculated for each particle as a function of LET. Single- and double-strand breaks (SSB and DSB), base release, and clustered DNA-lesions were computed from the Monte-Carlo based quantification of the reactive species and measured yields of the species responsible for the DNA lesion formation. The total amount of DNA damage depends on particle type and LET. The number of ionization events underestimates the quantity of DNA damage at LETs higher than 10 keV/μm. Minimum LETs of 9.4 and 11.5 keV/μm are required to induce clustered damage by a single track of proton and alpha particles, respectively. For a given radiation dose, an increase in LET reduces the number of particle tracks, leading to more complex clustered DNA damage, but a smaller number of separated clustered damage sites. The dependency of the number and the complexity of clustered DNA damage on LET and fluence suggests that the quantification of this damage can be a useful method for the estimation of the biological effectiveness of radiation. These results also suggest that medium-LET particles are more appropriate for the treatment of bulk targets, whereas high-LET particles can be more effective for small targets.

HPC atomic simulations of defect formation and kinetic Monte Carlo simulation of material ageing

Kinetic Monte Carlo (KMC) simulations are developed to simulate microstructure evolution under irradiation of structural materials of nuclear power plants. Methods based on rigid lattice atomic KMC and object KMC, despite some approximations, present the advantage to reach significant time, hence irradiation doses. The physical inputs such as the primary damage and defect cluster properties are the results of intensive atomic simulation on high performance computers. Here, atomic KMC is applied to model microstructure evolution of reactor pressure vessel steels and object KMC is applied to zirconium cladding materials.