Historically, animal numbers have most often been in the hundreds for experiments designed to estimate the dose reduction factor (DRF) of a radiation countermeasure treatment compared to a control treatment. Before 2010, researchers had to rely on previous experience, both from others and their own, to determine the number of animals needed for a DRF experiment. In 2010, a formal sample size formula was developed by Kodell et al. This theoretical work showed that sample sizes for realistic, yet hypothetical, DRF experiments could be less than a hundred animals and still have sufficient power to detect clinically meaningful DRF values. However, researchers have been slow to use the formula for their DRF experiments, whether from ignorance to its existence or hesitancy to depart from “tried and true” sample sizes. Here, we adapt the sample size formula to better fit usual DRF experiments, and, importantly, we provide real experimental evidence from two independent DRF experiments that sample sizes smaller than what have typically been used can still statistically detect clinically meaningful DRF values. In addition, we update a literature review of DRF experiments which can be used to inform future DRF experiments, provide answers to questions that researchers have asked when considering sample size calculations rather than solely relying on previous experience, whether their own or others', and, in the supplementary material (RADE-22-00124.1.S1.pdf), provide R code implementing the formula, along with several exercises to familiarize the user with the adapted formula.

Prediction of cancer risk from space radiation exposure is critical to ensure spaceflight crewmembers are adequately informed of the risks they face when accepting assignments to ambitious long-duration exploratory missions. Although epidemiological studies have assessed the effects of exposure to terrestrial radiation, no robust epidemiological studies of humans exposed to space radiation exist to support estimates of the risk from space radiation exposure. Mouse data derived from recent irradiation experiments provides valuable information to successfully develop mouse-based excess risks models for assessing relative biological effectiveness for heavy ions that can provide information to scale unique space radiation exposures so that excess risks estimated for terrestrial radiation can be adjusted for space radiation risk assessment. Bayesian analyses were used to simulate linear slopes for excess risk models with several different effect modifiers for attained age and sex. Relative biological effectiveness values for all-solid cancer mortality were calculated from the ratio of the heavy-ion linear slope to the gamma linear slope using the full posterior distribution and resulted in values that were substantially lower than what is currently applied in risk assessment. These analyses provide an opportunity to improve characterization of parameters used in the current NASA Space Cancer Risk (NSCR) model and generate new hypotheses for future animal experiments using out-bred mouse populations.

Heavy-ion radiation received during radiotherapy as well as the heavy-ion radiation received during space flight are equally considered harmful. Our previous study showed that TLR4 low toxic agonist, monophosphoryl lipid A (MPLA), alleviated radiation injury resulting from exposure to low-LET radiation. However, the role and mechanism of MPLA in heavy-ion-radiation injury are unclear. This study aimed to investigate the role of MPLA on radiation damage. Our data showed that MPLA treatment alleviated the heavy-ion-induced damage to microstructure and the spleen and testis indexes. The number of karyocytes in the bone marrow from the MPLA-treated group was higher than that in the irradiated group. Meanwhile, western blotting analysis of intestine proteins showed that pro-apoptotic proteins (cleaved-caspase3 and Bax) were downregulated while anti-apoptotic proteins (Bcl-2) were upregulated in the MPLA-treated group. Our in vitro study demonstrated that MPLA significantly improved cell proliferation and inhibited cell apoptosis after irradiation. Moreover, immunofluorescence staining and quantification of nucleic γ-H2AX and 53BP1 foci also suggested that MPLA significantly attenuated cellular DNA damage repair. Collectively, the above evidence supports the potential ability of MPLA to protect against heavy-ion-radiation injury by inhibiting apoptosis and alleviating DNA damage in vivo and vitro, which could be a promising medical countermeasure for the prevention of heavy-ion-radiation injury.

This study aims to provide a model that compounds historically proposed ideas regarding cell survival irradiated with X rays or particles. The parameters used in this model have simple meanings and are closely related to cell death-related phenomena. The model is adaptable to a wide range of doses and dose rates and thus can consistently explain previously published cell survival data. The formulas of the model were derived by using five basic ideas: 1. “Poisson's law”; 2. “DNA affected damage”; 3. “repair”; 4. “clustered affected damage”; and 5. “saturation of reparability”. The concept of affected damage is close to but not the same as the effect caused by the double-strand break (DSB). The parameters used in the formula are related to seven phenomena: 1. “linear coefficient of radiation dose”; 2. “probability of making affected damage”; 3. “cell-specific repairability”, 4. “irreparable damage by adjacent affected damage”; 5. “recovery of temporally changed repairability”; 6. “recovery of simple damage which will make the affected damage”; 7. “cell division”. By using the second parameter, this model includes cases where a single hit results in repairable–lethal and double-hit results in repairable–lethal. The fitting performance of the model for the experimental data was evaluated based on the Akaike information criterion, and practical results were obtained for the published experiments irradiated with a wide range of doses (up to several 10 Gy) and dose rates (0.17 Gy/h to 55.8 Gy/h). The direct association of parameters with cell death-related phenomena has made it possible to systematically fit survival data of different cell types and different radiation types by using crossover parameters.

Radiation-induced esophageal injury (RIEI) is a major dose-limiting complication of radiotherapy, mainly acute esophagitis. However, understanding of radiation injury and repair mechanisms in esophageal epithelial cells remains limited. MiR-132-3p and its uridylated isoform (miR-132-3p-UUU) are upregulated in radiation esophageal injury, yet their role in radiation-induced esophageal injury progression remains unexplored. We expressed miR-132-3p and its uridine form in irradiated human esophageal epithelial cells (HEEC) and secreted exosomes was examined by real-time polymerase chain reaction (RT-PCR). Cell proliferation, migration, apoptosis and colony formation were used to determine biological effects. Cell cycle assays and dual luciferase reporter assays were used to assess the relationship between miR-132-3p and its uridylated isoforms and MEF2A. The addition of miR-132-3p mimics or overexpression of miR-132-3p significantly inhibited the proliferation and migration of esophageal epithelial cells (HEEC cells as well as primary cells) and increased radiation damage. This was reversed by its uridylated isoform by reducing binding to MEF2A and regulating the cell cycle. Furthermore, miR-132-3p and its triuridylated isomer also regulate apoptosis after irradiation through pathways other than reactive oxygen species (ROS). In conclusion, our data reveal that radiation-induced miR-132-3p uridylation and exosome-mediated intercellular communication and tri-uridylated isoforms are protective against radiation-induced esophageal injury. Furthermore, miR-132-3p offers new opportunities as a promising biomarker widely present in human body fluids for the prediction of radiation esophagitis as a biomarker.

Previous publications describe the estimation of the dose from ionizing radiation to the whole lens or parts of it but have not considered other eye tissues that are implicated in cataract development; this is especially critical for low-dose, low-ionizing-density exposures. A recent review of the biological mechanisms of radiation-induced cataracts showed that lenticular oxidative stress can be increased by inflammation and vascular damage to non-lens tissues in the eye. Also, the radiation oxygen effect indicates different radiosensitivities for the vascular retina and the severely hypoxic lens. Therefore, this study uses the Monte Carlo N-Particle simulations to quantify dose conversion coefficients for several eye tissues for incident antero-posterior exposure to electrons, photons, and neutrons (and the tertiary electron component of neutron exposure). A stylized, multi-tissue eye model was developed by modifying a model by Behrens et al. (2009) to include the retina, uvea, sclera, and lens epithelial cell populations. Electron exposures were simulated as a single eye, whereas photon and neutron exposures were simulated employing two eyes embedded in the ADAM-EVA phantom. For electrons and photons, dose conversion coefficients are highest for either anterior tissues for low-energy incident particles or posterior tissues for high-energy incident particles. Neutron dose conversion coefficients generally increase with increasing incident energy for all tissues. The ratio of the absorbed dose delivered to each tissue to the absorbed dose delivered to the whole lens demonstrated the considerable deviation of non-lens tissue doses from lens doses, depending on particle type and its energy. These simulations demonstrate that there are large variations in the dose to various ocular tissues depending on the incident radiation dose coefficients; this large variation will potentially impact cataract development.

The mesh-type models are superior to voxel models in cellular dose assessment coupled with Monte Carlo codes. The aim of this study was to expand the micron-scale mesh-type models based on the fluorescence tomography of real human cells, and to investigate the feasibility of these models in the application of various irradiation scenarios and Monte Carlo codes. Six different human cell lines, including pulmonary epithelial BEAS-2B, embryonic kidney 293T, hepatocyte L-02, B-lymphoblastoid HMy2.CIR, Gastric mucosal GES-1, and intestine epithelial FHs74Int, were adopted for single mesh-type models reconstruction and optimization based on laser confocal tomography images. Mesh-type models were transformed into the format of polygon mesh and tetrahedral mesh for the GATE and PHITS Monte Carlo codes, respectively. The effect of model reduction was analyzed by dose assessment and geometry consideration. The cytoplasm and nucleus doses were obtained by designating monoenergetic electrons and protons as external irradiation, and S values with different “target-source” combinations were calculated by assigning radioisotopes as internal exposure. Four kinds of Monte Carlo codes were employed, i.e., GATE with “Livermore,” “Standard” and “Standard and Geant4-DNA mixed” models for electrons and protons, as well as PHITS with “EGS” mode for electrons and radioisotopes. Multiple mesh-type real human cellular models can be applied to Monte Carlo codes directly without voxelization when combined with certain necessary surface reduction. Relative deviations between different cell types were observed among various irradiation scenarios. The relative deviation of nucleus S value reaches up to 85.65% between L-02 and GES-1 cells by ³H for the “nucleus-nucleus” combination, while that of 293T and FHs74Int nucleus dose for external beams at a 5.12 cm depth of water is 106.99%. Nucleus with smaller volume is far more affected by physical codes. There is a considerable deviation for dose within BEAS-2B at the nanoscale. The multiple mesh-type real cell models were more versatile than voxel models and mathematical models. The present study provided several models which can easily be extended to other cell types and irradiation scenarios for RBE estimations and biological effect predictions, including radiation biological experiments, radiotherapy and radiation protection.

For radiation protection purposes, noncancer effects with a threshold-type dose-response relationship have been classified as tissue reactions (formerly called nonstochastic or deterministic effects), and equivalent dose limits aim to prevent occurrence of such tissue reactions. Accumulating evidence demonstrates increased risks for several late occurring noncancer effects at doses and dose rates much lower than previously considered. In 2011, the International Commission on Radiological Protection (ICRP) issued a statement on tissue reactions to recommend a threshold of 0.5 Gy to the lens of the eye for cataracts and to the heart and brain for diseases of the circulatory system (DCS), independent of dose rate. Literature published thereafter continues to provide updated knowledge. Increased risks for cataracts below 0.5 Gy have been reported in several cohorts (e.g., including in those receiving protracted or chronic exposures). A dose threshold for cataracts is less evident with longer follow-up, with limited evidence available for risk of cataract removal surgery. There is emerging evidence for risk of normal-tension glaucoma and diabetic retinopathy, but the long-held tenet that the lens represents among the most radiosensitive tissues in the eye and in the body seems to remain unchanged. For DCS, increased risks have been reported in various cohorts, but the existence or otherwise of a dose threshold is unclear. The level of risk is less uncertain at lower dose and lower dose rate, with the possibility that risk per unit dose is greater at lower doses and dose rates. Target organs and tissues for DCS are also unknown, but may include heart, large blood vessels and kidneys. Identification of potential factors (e.g., sex, age, lifestyle factors, coexposures, comorbidities, genetics and epigenetics) that may modify radiation risk of cataracts and DCS would be important. Other noncancer effects on the radar include neurological effects (e.g., Parkinson's disease, Alzheimer's disease and dementia) of which elevated risk has increasingly been reported. These late occurring noncancer effects tend to deviate from the definition of tissue reactions, necessitating more scientific developments to reconsider the radiation effect classification system and risk management. This paper gives an overview of historical developments made in ICRP prior to the 2011 statement and an update on relevant developments made since the 2011 ICRP statement.