Radiation and Environmental Biophysics最新文献

Radiation therapy (RT) is fundamental to the fight against cancer because of its exceptional ability to target and destroy cancer cells. However, conventional radiation therapy can significantly affect the adjacent normal tissues, leading to fibrosis, inflammation, and decreased organ function. This tissue damage not only reduces the quality of life but also prevents the total elimination of cancer. The transformation of epithelial cells into mesenchymal-like cells, termed epithelial-mesenchymal transition (EMT), is essential for processes such as fibrosis, embryogenesis, and wound healing. Conventional radiation therapy increases the asymmetric activation of fibrotic and inflammatory pathways, and the resulting chronic fibrotic changes and organ dysfunction are linked to radiation-induced epithelial-mesenchymal transition. Recent advances in radiation therapy, namely flash radiation therapy (FLASH-RT), have the potential to widen the therapeutic index. Radiation delivered by FLASH-RT at very high dose rates (exceeding 40 Gy/s) can protect normal tissue from radiation-induced damage, a phenomenon referred to as the "FLASH effect". Preclinical studies have demonstrated that FLASH-RT successfully inhibits processes associated with fibrosis and epithelial-mesenchymal transition, mitigates damage to normal tissue, and enhances regeneration. Three distinct types of EMT have been identified: type-1, associated with embryogenesis; Type-2, associated with injury potential; and type-3, related with cancer spread. The regulation of EMT via pathways, including TGF-β/SMAD, WNT/β-catenin, and NF-κB, is essential for radiation-induced tissue remodelling. This study examined radiation-induced EMT, TGF-β activity, multiple signalling pathways in fibrosis, and the potential of FLASH-RT to reduce tissue damage. FLASH-RT is a novel approach to treat chronic tissue injury and fibrosis post-irradiation by maintaining epithelial properties and regulating mesenchymal markers including vimentin and N-cadherin. Understanding these pathways will facilitate the development of future therapies that can alleviate fibrosis, improve the efficacy of cancer therapy, and improve the quality of life of patients.

Most studies on the effects of galactic cosmic rays (GCR) have relied on terrestrial irradiation using spatially homogeneous dose distributions of mono-energetic beams comprised of one ion species. Here, we exposed mice to novel beams that more closely mimic GCR, namely, comprising poly-energetic ions of multiple species. Six-month-old male and female C57BL/6J mice were exposed to 0 Gy, 0.5 Gy, or 1.5 Gy simplified simulated 5 ion GCR (GCRsim). Exposure to microgravity was simulated using hindlimb unloading (HLU). At nine months post exposure, the mice were terminated to assess for the presence of exposure-induced epigenetic alterations. DNA hypermethylation in the 5'-untranslated regions of Lx_III, MdFanc_I, and MdMus_II families of the Long Interspersed Nucleotide Element 1 (LINE-1) was observed in the lungs of male mice. These effects were accompanied by increases in the expression of DNA methyltransferases Dnmt1 and Dnmt3a, and methyl-binding protein, MecP2. Trends towards DNA hypomethylation, although insignificant, were observed in the lungs of female mice in the HLU + 1.5 Gy GCRsim group. Altogether, our findings suggest persistent and sex-specific epigenetic reprogramming in the mouse lung and suggests that the DNA methylation status of LINE-1 can serve as a robust and reliable biomarker of previous radiation exposure.

This study presents a novel approach to skin toxicity assessment in preclinical radiotherapy trials through an advanced imaging setup and deep learning. Skin reactions, commonly associated with undesirable side effects in radiotherapy, were meticulously evaluated in 160 mice across four studies. A comprehensive dataset containing 7542 images was derived from proton/electron trials with matched manual scoring of the acute toxicity on the right hind leg, which was the target area irradiated in the trials. This dataset was the foundation for the subsequent model training. The two-step deep learning framework incorporated an object detection model for hind leg detection and a classification model for toxicity classification. An observer study involving five experts and the deep learning model, was conducted to analyze the retrospective capabilities and inter-observer variations. The results revealed that the hind leg object detection model exhibited a robust performance, achieving an accuracy of almost 99%. Subsequently, the classification model demonstrated an overall accuracy of about 85%, revealing nuanced challenges in specific toxicity grades. The observer study highlighted high inter-observer agreement and showcased the model's superiority in accuracy and misclassification distance. In conclusion, this study signifies an advancement in objective and reproducible skin toxicity assessment. The imaging and deep learning system not only allows for retrospective toxicity scoring, but also presents a potential for minimizing inter-observer variation and evaluation times, addressing critical gaps in manual scoring methodologies. Future recommendations include refining the system through an expanded training dataset, paving the way for its deployment in preclinical research and radiotherapy trials.

Radiation quality for determining biological effects is commonly linked to the microdosimetric quantity lineal energy ( $y$ ) and to the dose-mean lineal energy ( $y_{\text{D}}$ ). Calculations of $y_{\text{D}}$ are typically performed by specialised Monte Carlo track-structure (MCTS) codes, which can be time-intensive. Thus, microdosimetry-based analytic models are potentially useful for practical calculations. Analytic model calculations of proton $y_{\text{D}}$ and radiation protection quality factor ( $Q$ ) values in sub-micron liquid water spheres (diameter 10-1000 nm) over a broad energy range (1 MeV-1 GeV) are compared against MCTS simulations by PHITS, RITRACKS, and Geant4-DNA. Additionally, an improved analytic microdosimetry model is proposed. The original analytic model of Xapsos is refined and model parameters are updated based on Geant4-DNA physics model. Direct proton energy deposition is described by an alternative energy-loss straggling distribution and the contribution of secondary electrons is calculated using the dielectric formulation of the relativistic Born approximation. MCTS simulations of proton $y_{\text{D}}$ values using the latest versions of the PHITS, RITRACKS, and Geant4-DNA are reported along with the Monte Carlo Damage Simulation (MCDS) algorithm. The $y_{\text{D}}$ datasets are then used within the Theory of Dual Radiation Action (TDRA) to illustrate variations in $Q$ with proton energy. By a careful selection of parameters, overall differences at the ~ 10% level between the proposed analytic model and the MCTS codes can be attained, significantly improving upon existing models. MCDS estimates of $y_{\text{D}}$ are generally much lower than estimates from MCTS simulations. The differences of $Q$ among the examined methods are somewhat smaller than those of $y_{\text{D}}$ . Still, estimates of proton $Q$ values by the present model are in better agreement with MCTS-based estimates than the existing analytic models. An improved microdosimetry-based analytic model is presented for calculating proton $y_{\text{D}}$ values over a broad range of proton energies (1 MeV-1 GeV) and target sizes (10-1000 nm) in very good agreement with state-of-the-art MCTS simulations. It is envisioned that the proposed model might be used as an alternative to CPU-intensive MCTS simulations and advance practical microdosimetry and quality factor calculations in medical, accelerator, and space radiation applications.

This study explores the development and efficacy of eggshell-derived particle composites with epoxy resin for enhanced radiation shielding applications. Eggshells, primarily composed of calcium carbonate, were processed into particles of three sizes: small, medium, and large. These particles were incorporated into epoxy resin at a 50% weight ratio and characterized using a Laser Particle Size Distribution Analyzer. Radiation shielding properties were determined using diagnostic X-ray equipment and a Radcal Accu-Gold detector, evaluating attenuation parameters such as the Half-Value Layer (HVL) and Linear Attenuation Coefficient (LAC). Mechanical testing revealed that composites with large particles exhibited the weakest performance, with a maximum force of 5674 N and stress of 52 MPa. In contrast, small particle composites demonstrated superior mechanical properties, achieving a maximum force of 9125 N and stress of 97 MPa. Additionally, small particle composites (S50%) displayed the highest LAC and lowest HVL, confirming their superior radiation shielding efficiency due to better dispersion and increased surface area. These findings highlight the potential of using finely ground eggshell particles to create cost-effective, environmentally friendly materials for radiation protection, underscoring the importance of particle size optimization in the development of advanced composite materials.

Goal of the present study was to develop and build a phantom that replicates the air gaps under a gel bolus and to estimate the surface dose (D_surf) under normal incidence with a 6 MV photon beam. For this, an acrylic phantom with 10 plates, each including five open slots (one in the centre and four off axis) with a size of 2 cm × 2 cm at depths of 0.54 cm, 0.72 cm, 0.90 cm, 1.26 cm, and 1.62 cm from the phantom's surface was used. Computed tomography image sets were obtained without and with a gel bolus (thickness: 2 mm, 4 mm, and 6 mm) placed on top of the phantom. Dose calculations were performed with the XiO treatment planning system (TPS) for a 6 MV photon beam at normal incidence and a field size of 15 cm × 15 cm that covered all the slots. A virtual bolus in TPS was employed in CT picture sets that did not include a bolus. Six points of interest at a depth of 1 mm from the surface contour of each slot were used to determine the mean surface dose (D_surf) estimated by the TPS with and without the presence of a bolus. It turned out that, as the depth of the air gap (between skin surface and bolus surface) increased from 0.54 cm to 1.62 cm, there was a 25.2% increase in D_surf without bolus, followed by an increase of 7.6%, 6.4%, and 7.7% for a virtual bolus with 2 mm, 4 mm, and 6 mm thickness, while corresponding increases were 14.8%, 14.3%, and 8.3% for an actual bolus, respectively. However, as the thickness of the air gap increased, D_surf under the bolus decreased (from - 17.5% to -18.8%, and from - 10.4% to -16.9%, for a virtual and a physical bolus, respectively). It is concluded that, to ensure a homogeneous D_surf across the treatment area, extra attention should be given while utilizing a bolus in clinical radiation applications, to avoid any air gaps under the bolus.

The Canadian Guidelines for the Management of Naturally Occurring Radioactive Materials (NORM) have been developed to manage radiation doses received in workplaces involving NORM, such as mineral extraction and processing, oil and gas production, metal recycling or water treatment facilities. This management strategy works well for most naturally occurring radioactive materials in workplaces, with the exception of radon. Radon is a naturally occurring radioactive gas generated by the decay of uranium-bearing minerals in rocks and soils. Because radon exists everywhere in varying concentrations, it is not feasible to use incremental radon generated or enhanced by a practice as a means for assessing the need for radon management programs. Drawing from lessons learned through implementing the current NORM Guidelines, we propose decoupling the decision thresholds for NORM management (excluding radon) and radon management so that the two are considered separately, and quantifying decision-points for managing occupational radon exposure as average annual activity concentrations, with no requirement for dose calculations. Proposed application of this approach in the updated Canadian NORM Guidelines is described.

Increased thyroid cancer incidence has been one of the principal adverse health effects of the Chornobyl (Chernobyl) nuclear power plant accident. Accurate dose estimation is critical for assessing the radiation dose-response relationship. Current dosimetry estimates for individuals from the Chornobyl Tissue Bank (CTB) are based only on the limited information on their places of residence at the time of the accident and/or at the time of surgery for thyroid cancer. The present study aimed to assess whether additional residential and dietary history data collected during personal interviews would substantially impact dose estimates. This paper presents an assessment of thyroid doses from ¹³¹I intake for the 197 exposed individuals from the CTB with pathologically confirmed papillary thyroid cancer. Thyroid doses, which had been calculated for these individuals in 2010, were revised in this study using the recently substantially revised 'Thyroid Dosimetry 2020 system for Ukraine' (TDU20). In addition, residence and diet history data were collected during personal interviews with individuals for whom dosimetry-related data were scarce. The arithmetic mean of thyroid doses estimated in this study was 510 mGy (previously 700 mGy), while the median was 81 mGy (previously 120 mGy). A rather wide range of thyroid doses from zero to 11.9 Gy (previously up to 15.0 Gy) was observed among study participants. The uncertainties in doses were characterized by the geometric standard deviation of 1,000 individual stochastic doses. As a result, the geometric standard deviation varied from 1.3 to 5.3 with an overall arithmetic mean of 2.7 and a median of 2.9. This study clearly showed that the use of individual questionnaire data in dose assessment of individuals who completed personal dosimetry interviews had a noticeable impact on the thyroid dose values: the thyroid doses changed by more than 100 mGy in 31 out of 104 (29.8% of the total) individuals, while such changes due to the use of TDU20 were observed in 18 out of 104 (17.3%) individuals. Clearly, future focused studies using samples from the CTB would benefit from personal interviews to improve dose estimates. Another lesson learned from this study is that whenever a radiation accident occurs, it is important to ask affected people by health and radiation safety authorities to keep records of their own behavior and diet, and, if possible, those of their children.

This study investigates the ²¹⁰Pb activity concentrations in tobacco and cigarettes available in Slovakia, utilizing two specific extraction methods including the Sr Resin sorbent used in extraction chromatography, and the AnaLig Sr01 sorbent, which operates based on molecular recognition principles. The findings revealed significant variations in ²¹⁰Pb activity concentrations, with concentrations ranging from 13.3 to 33.8 mBq/g in tobacco, and from 16.8 to 28.5 mBq/g in cigarettes. The average ²¹⁰Pb activity per cigarette was 14.4 mBq ± 1.7 mBq. Annual effective doses for smokers were calculated, with values for tobacco ranging from 27.9 to 126.7 µSv and for cigarettes from 25.5 to 115.7 µSv. The study highlights the importance of comparing these two methods to ensure an accurate assessment of ²¹⁰Pb exposure and evaluation of radiological risks associated with smoking in Slovakia.