A comparative study on the dose-effect of low-dose radiation based on microdosimetric analysis and single-cell sequencing technology.

The biological mechanisms triggered by low-dose exposure still need to be explored in depth. In this study, the potential mechanisms of low-dose radiation when irradiating the BEAS-2B cell lines with a Cs-137 gamma-ray source were investigated through simulations and experiments. Monolayer cell population models were constructed for simulating and analyzing distributions of nucleus-specific energy within cell populations combined with the Monte Carlo method and microdosimetric analysis. Furthermore, the 10 × Genomics single-cell sequencing technology was employed to capture the heterogeneity of individual cell responses to low-dose radiation in the same irradiated sample. The numerical uncertainties can be found both in the specific energy distribution in microdosimetry and in differential gene expressions in radiation cytogenetics. Subsequently, the distribution of nucleus-specific energy was compared with the distribution of differential gene expressions to guide the selection of differential genes bioinformatics analysis. Dose inhomogeneity is pronounced at low doses, where an increase in dose corresponds to a decrease in the dispersion of cellular-specific energy distribution. Multiple screening of differential genes by microdosimetric features and statistical analysis indicate a number of potential pathways induced by low-dose exposure. It also provides a novel perspective on the selection of sensitive biomarkers that respond to low-dose radiation.

Quantitative assessment of corneal elasticity distribution after FS-LASIK using optical coherence elastography.

Quantifying corneal elasticity after femtosecond laser-assisted in situ keratomileusis (FS-LASIK) procedure plays an important role in improving surgical safety and quality, since some latent complications may occur ascribing to changes in postoperative corneal biomechanics. Nevertheless, it is suggested that current research has been severely constrained due to the lack of an accurate quantification method to obtain postoperative corneal elasticity distribution. In this paper, an acoustic radiation force optical coherence elastography system combined with the improved phase velocity algorithm was utilized to realize elasticity distribution images of the in vivo rabbit cornea after FS-LASIK under various intraocular pressure levels. As a result, elasticity variations within and between the regions of interest could be identified precisely. This is the first time that elasticity imaging of in vivo cornea after FS-LASIK surgery was demonstrated, and the results suggested that this technology may hold promise in further exploring corneal biomechanical properties after refractive surgery.

[Fraction Characteristic and Risk Assessment of Heavy Metals in Surface Sediments of the Yellow River Mainstream].

Heavy metals(HMs) are highly toxic and do not easily degrade in the environment. They can accumulate in the human body through the food chain, with serious impacts on the ecological environment and human health. In this study, 14 sampling sites along the mainstream of the Yellow River were investigated, and the total content and chemical fractions of six heavy metals(As, Cd, Cr, Cu, Pb, and Zn) in sediments were analyzed. The geo-accumulation index, potential ecological risk index, and risk assessment coding were used to assess the contamination level and bioavailability of HMs in sediment. Principal component analysis and redundancy analysis were used to identify the main sources of HMs. The results showed that the average content of heavy metals was in the order of Cr>Zn>Cu>Pb>As>Cd. Cd had the highest excess rate relative to the background value of each reach, reaching 85.7%. In the sediments, As, Zn, Pb, and Cu were predominantly in the oxidizable fraction(F3:sulfide and organic matter-bound), Cd was mainly occupied by the acid-soluble(F1:exchangeable and carbonate-bound) and a residual fraction(F4:mineral matrix-bound), and Cr was predominantly in the residual fraction. As, Cr, Cu, Pb, and Zn showed the lowest bioavailability in the upstream, increased in the midstream, and finally decreased in the downstream. The risk assessment showed that Cd, the element with the highest pollution risk level in the Yellow River, was prone to pose a serious threat to the ecological environment and should be prevented and controlled first. The PCA and RDA analyses revealed that fine sediment and total organic matter controlled HMs contamination. Therefore, the prevention and control of soil erosion and sediment migration should be emphasized to control HMs pollution in the Yellow River Basin.

Microdosimetric assessment about proton spread-out Bragg peak at different depths based on the normal human mesh-type cell population model.

Objective.In clinical proton therapy, the spread-out Bragg peak (SOBP) is commonly used to fit the target shape. Dose depositions at microscopic sites vary, even with a consistent absorbed dose (D) in SOBP. In the present study, monolayer mesh-type cell population models were developed for microdosimetric assessment at different SOBP depths.Approach.Normal human bronchial epithelial (BEAS-2B) and hepatocytes (L-O2) mesh-type cell models were constructed based on fluorescence tomography images of normal human cells. Particle transport simulation in cell populations was performed coupled with Monte Carlo software PHITS. The relationship between microdosimetry and macrodosimetry of SOBP at different depths was described by analyzing the microdosimetric indicators such as specific energyz,specific energy distributionfz,D,and relative standard deviationσz/z¯within cells. Additionally, the microdosimetric distributions characteristics and their contributing factors were also discussed.Main results.The microscopic dose distribution is strongly influenced by cellular size, shape, and material. The mean specific energyz¯of nucleus and cytoplasm in the cell population is greater than the overall absorbed dose of the cell population model (Dp), with a maximumz¯/Dpof 1.1. The cellular dose distribution is different between the BEAS-2B mesh-type model and its concentric ellipsoid geometry-type model, which difference inz¯is about 10.3% for the nucleus and about 7.5% for the cytoplasm with the SOBP depth of 15 cm. WhenD= 2 Gy, the maximumzof L-O2 nucleus reaches 2.8 Gy andσz/z¯is 5.1% at the mid-depth SOBP (16-18 cm); while the maximumzof the BEAS-2B nucleus reaches 2.2 Gy with only 2.7% ofσz/z¯.Significance.The significant variation of microdosimetric distributions of SOBP different depths indicates the necessity to use mesh-type cell population models, which have the potential to be compared with biological results and build the bio-physical model.

Multiple Mesh-type Real Human Cell Models for Dosimetric Application Coupled with Monte Carlo Simulations.

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.

Research on the proximity functions of microdosimetry of low energy electrons in liquid water based on different Monte Carlo codes.

PURPOSE: The proximity function is an important index in microdosimetry for describing the spatial distribution of energy, which is closely related to the biological effects of organs or tissues in the target area. In this work, the impact of parameters, such as physic models, cut-off energy, and initial energy, on the proximity function are quantitated and compared. METHODS: According to the track structure (TS) and condensed history (CH) low-energy electromagnetic models, this paper chooses a variety of Monte Carlo (Monte Carlo, MC) codes (Geant4-DNA, PHITS, and Penelope) to simulate the track structure of low-energy electrons in liquid water and evaluates the influence of the electron initial energy, cut-off energy, energy spectrum, and physical model factors on the differential proximity function. RESULTS: The results show that the initial energy of electrons in the low-energy part (especially less than 1 keV) has a greater impact on the differential proximity function, and the choice of cut-off energy has a greater impact on the differential proximity function corresponding to small radius sites (generally less than 10 nm). The difference in the electronic energy spectrum has little effect on the result, and the proximity functions of different physics models show better consistency under large radius sites. CONCLUSIONS: This work comprehensively compares the differential proximity functions under different codes by setting a variety of simulation conditions and has basic guiding significance for helping users simulate and analyze the deposition characteristics of microscale electrons according to the selection of an appropriate methodology and cut-off energy.

THE APPLICATION OF NEURAL NETWORK TECHNOLOGY BASED ON MEA-BP ALGORITHM IN THE PREDICTION OF MICRODOSIMETRIC QUALITIES.

The most abundant products of the interaction between radiation and matter are low-energy electrons, and the collisions between these electrons and biomolecules are the main initial source of radiation-based biological damage. To facilitate the rapid and accurate quantification of low-energy electrons (0.1-10 keV) in liquid water at different site diameters (1-2000 nm), this study obtained ${\overline{y}}_{\mathrm{F}}$ and ${\overline{y}}_{\mathrm{D}}$data for low-energy electrons under these conditions. This paper proposes a back-propagation (BP) neural network optimized by the mind evolutionary algorithm (MEA) to construct a prediction model and evaluate the corresponding prediction effect. The results show that the ${\overline{y}}_{\mathrm{F}}$ and ${\overline{y}}_{\mathrm{D}}$ values predicted by the MEA-BP neural network algorithm reach a training precision on the order of ${10}^{-8}$. The relative error range between the prediction results of the validated model and the Monte Carlo calculation results is 0.03-5.98% (the error range for single-energy electrons is 0.1-5.98%, and that for spectral distribution electrons is 0.03-4.4%).

Cellular S-value evaluation based on real human cell models using the GATE MC package.

Exploring the spatial distribution of the energy loss of ionising radiation at the subcellular level is indispensable for evaluating the radiobiological effects of targeted radionuclide therapy accurately. Believing that S-values are important for obtaining the target dose, the Committee on Medical Internal Radiation Dose (MIRD) proposed a method to obtain the cellular dosimetric parameter. However, most available data on cellular S-values were calculated based on simple geometric models, such as ellipsoids or spheres, which do not accurately reflect biological reality. To investigate the influence of the cellular model on S-values, calculations were performed for two kinds of polygon-surface phantom models of realistic, individual human cells, the lung epithelial cell model (the B2B Phantom model) and the hepatocyte model (the Liver Phantom model), using the Monte Carlo (MC) software package GATE. To analyse the influence of cell geometry on the final S-value, the differences in the S-values between the realistic cell models and simple geometric sphere and ellipsoid models with similar volumes were calculated and compared for six different combinations of source and target regions. The irradiation conditions were 0.01-1.10 MeV monoenergetic electron sources and the Auger electronic therapy nuclides Ga-67, Tc-99m, In-111, I-125 and Tl-201, which are commonly used in nuclear medicine. The S-values calculated in this study are different from the results of the simple geometry models proposed by previous researchers. Two more precise polygon-surface phantom models of realistic, individual human cells were used, which provided more accurate information about the cell dose and will be very useful for the diagnostic application of radiotherapy in the future.