Bridging the translational gap in radiotherapy: a human three-dimensional cell culture for evaluating neutron biological effects

Bridging the translational gap in radiotherapy: a human three-dimensional cell culture for evaluating neutron biological effects | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Bridging the translational gap in radiotherapy: a human three-dimensional cell culture for evaluating neutron biological effects Susanna Leva, Kazuyo Igawa, Izumi Yamamoto, Yoshinori Sakurai, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9354079/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract In radiation therapy, accurately estimating the relative biological effectiveness (RBE) is essential for the safe and effective clinical application of neutron radiation therapy. Current RBE evaluations primarily rely on two-dimensional (2D) colony formation assays. However, these models cannot fully capture tissue-level complexity and are not applicable to normal cells lacking colony-forming ability. This limits their clinical applicability. This study demonstrated that the dimensionality of the culture is a critical determinant of radiation sensitivity. While the biological effectiveness of neutron irradiation is systematically overestimated in conventional 2D monolayer systems, three-dimensional (3D) tissue-mimicking models more accurately reproduce the resistance of normal tissues observed in clinical settings. Specifically, we identified a dose-dependent thinning of the extracellular matrix at doses of 25 Gy or higher, suggesting that neutron-induced damage extends beyond cell death to include structural and microenvironmental damage. These findings offer direct insights into the estimation of clinical doses and the protection of normal tissues. While further refinement of model parameters, including cell density and microenvironmental composition, is necessary, the proposed 3D platform provides a clinically meaningful framework for evaluating radiation-induced toxicity in non-colony-forming normal tissues. By facilitating a more precise evaluation of radiation-induced tissue effects, this methodology has the potential to enhance the estimation of RBE and risk stratification, thus contributing to the development of more secure treatment protocols and the broader implementation of neutron therapy. Biological sciences/Biophysics Biological sciences/Cancer Health sciences/Medical research Health sciences/Oncology Physical sciences/Physics Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Neutron radiobiology represents a distinctive paradigm within radiation science, defined by the unique physical interactions of neutrons with biological matter and the complex patterns of energy deposition that ensue 1 , 2 . Unlike photons or charged particles, which predominantly interact with atomic electrons, neutrons are indirectly ionizing and deposit energy through nuclear interactions, generating cascades of high-linear energy transfer (LET) secondary particles 3 . These processes give rise to densely clustered DNA damage, challenging canonical models of radiation response and repair. The biological consequences of neutron exposure span multiple domains, from space radiation biology, where secondary neutrons contribute substantially to astronaut risk 4 , to radiation protection in high-energy physics environments 5 – 7 . In oncology, these unique properties are harnessed therapeutically in boron neutron capture therapy (BNCT), a modality that exploits neutron capture reactions to achieve highly localized, cell-selective cytotoxicity 2 , 8 . However, a fundamental yet underappreciated aspect of neutron radiobiology is the intrinsic biological activity of thermal neutrons in native tissue environments, independent of exogenous boron delivery 3 . Thermal neutrons, despite their low kinetic energy (~ 0.025 eV), induce biologically significant effects through nuclear capture reactions with endogenous elements, particularly nitrogen and hydrogen. The ¹⁴N(n,p)¹⁴C reaction generates high-LET protons, whereas ¹H(n,γ)²H produces low-LET gamma radiation, together shaping a composite radiation field within tissues 1 , 9 . This duality underscores a key conceptual challenge: the biological effectiveness of neutrons cannot be fully understood through conventional radiobiological frameworks that are largely derived from photon-based systems 2 , 10 . Instead, neutron-induced damage reflects a multi-scale phenomenon, encompassing not only direct DNA damage but also perturbations of tissue architecture and microenvironmental integrity 11 , 12 . Consequently, accurate estimation of relative biological effectiveness (RBE) remains a central and unresolved issue in both radiation protection 7 and clinical translation 3 , 12 . Historically, the quantification of RBE has been conducted using two-dimensional (2D) monolayer cultures and clonogenic survival assays. Despite the fact that these approaches have yielded foundational insights, they are intrinsically reductionist and fail to capture the spatial, structural, and biochemical complexity of living tissues 14 . Notably, these models fail to incorporate the significance of cell-to-cell interactions and the influence of the extracellular matrix (ECM) on radiosensitivity. Furthermore, they do not consider the oxygen, nutrient, and signalling molecule gradients that have been identified as critical regulators of radiosensitivity 15 . The limitations of 2D systems have catalysed a paradigm shift toward three-dimensional (3D) tissue models, including spheroids and scaffold-based constructs, which more faithfully recapitulate tissue organization and microenvironmental heterogeneity. These models reveal that radiosensitivity is not an intrinsic cellular property alone but is emergent from multicellular architecture and context-dependent signalling networks 16 . As such, 3D systems offer a more physiologically relevant framework for interrogating neutron-induced biological effects and refining RBE estimation. Importantly, this transition from 2D to 3D models reframes neutron radiobiology as a systems-level problem, in which radiation effects must be understood across multiple spatial and temporal scales from molecular damage to tissue-level dysfunction 14 – 17 . Within this context, features such as extracellular matrix remodelling and microenvironmental disruption emerge as critical determinants of radiation response, extending beyond traditional endpoints based solely on clonogenic survival 15 , 18 – 20 . In this study, we address these conceptual and methodological gaps by systematically comparing the effects of thermal neutron irradiation in 2D and 3D culture systems. Using controlled neutron exposures at the Kyoto University Research Reactor (KUR), we investigate how culture dimensionality shapes radiosensitivity and biological response across clinically relevant dose ranges. Furthermore, we integrate quantitative validation strategies to ensure robust assessment within complex 3D architectures. By bridging physical dosimetry with advanced tissue-mimetic modelling, this work contributes to the emerging framework of next-generation radiobiology, in which experimentally tractable yet physiologically relevant systems are leveraged to refine risk assessment and inform precision radiotherapy strategies. Results 1. Evaluation of radiobiological response in 2D and 3D models of stromal and cancer cells The evaluation of survival fractions across a neutron dose range of 0 to 25.8 Gy revealed a consistent dose-dependent reduction in viability for all cell lines tested in 2D monolayers (Fig. 1 a, b). In the 2D stromal cell cultures, human umbilical vein endothelial cells (HUVEC) cells exhibited lower survival rates compared to patient-derived normal oral fibroblasts (NOF) and patient-derived cancer-associated fibroblasts (CAF), with a statistically significant difference emerging at 2.5 Gy (*p < 0.05) (Fig. 1 a). Similarly, the 2D cancer cell cultures showed a steady decrease in survival as the neutron dose increased, with lowly metastatic human oral squamous cell carcinoma (HSC-4) demonstrating higher radio sensitivity compared to the human osteosarcoma cells (MG-63) and highly metastatic human oral squamous cell carcinoma (HSC-3) at 2.5 Gy (**p < 0.01) (Fig. 1 b). Complementary morphological characterization of 2D monolayers and detailed viability metrics, including live cell percentage and mean cell diameter, are provided ( Supplementary Fig. 1, 2 ). For stromal cells cultured in a 3D model, the decrease in survival rate was attenuated with increasing neutron dose (Fig. 1 c, d). In this 3D stromal environment, no significant differences were observed among the cell lines (Fig. 1 c). Furthermore, no apparent reduction in survival rate was observed in the 3D tumour model (Fig. 1 d). Despite this overall stability specific significant differences were observed at low doses, particularly at 2.5 Gy (****p < 0.0001) and 5.3 Gy (*p < 0.05), where HSC-4 showed a higher survival compared to HSC-3 and MG-63. The direct comparison between 2D and 3D cultures across the different neutron radiation doses (2.5, 5.3, 13.2, and 25.8 Gy) revealed a significant divergence in survival profiles for most cell lines (Fig. 1 e, h). At the dose of 2.5 Gy, a significant increase in radio resistance was observed in the 3D models for HSC-4 (****p < 0.0001), and HUVEC (**p < 0.01) compared to their 2D counterparts (Fig. 1 e). This lower response of the cells in 3D environment was further confirmed at 5.3 Gy, where the divergence reached maximum significance for HUVEC, and HSC-3 (****p < 0.0001), while HSC-4 and MG-63 also showed a significant difference (**p < 0.01) (Fig. 1 f). At 13.2 Gy, the response reached a peak of divergence, with all cancer and stromal lines, excluding NOF and CAF, showing the maximum level of statistical significance (****p < 0.0001) (Fig. 1 g). At 25.8 Gy, the statistical profile shifted: while a maximum divergence was maintained for HSC-3, MG-63, and HUVEC (****p < 0.0001), the difference between 2D and 3D survival for HSC-4, though still significant, was characterized by a lower level of significance (**p < 0.01) (Fig. 1 h). In contrast, the NOF and CAF lines demonstrated a remarkably stable response regardless of the culture system. Across the entire neutron dose range, no significant differences were observed between the 2D and 3D configurations for these two patient delivered cells (Fig. 1 e, h). Both NOF and CAF consistently exhibited an intrinsic radio resistance, with a low reduction in viability that remained independent of the culture model. 2. Histological assessment of 3D scaffolds in cancer and stromal cell models The structural impact of neutron irradiation on the 3D models was evaluated by integrating qualitative histological observations with a quantitative approach to measure tissue parameters. As demonstrated in the representative sections of the 3D cancer scaffolds, there is a visible and progressive contraction of the scaffold matrix as the neutron dose increases from 0 to 25.8 Gy (Fig. 2 a). For the stromal models (NOF, CAF, HUVEC), this structural response was confirmed by the quantitative analysis of scaffold thickness, where a dose-dependent thinning is recorded for all stromal lines (Fig. 2 b). Parallel to the matrix contraction, the nuclear count analysis indicated that the total number of stromal cells within the 3D environment underwent a slight reduction in a dose dependent manner (Fig. 2 c). A similar pattern was observed for the 3D cancer scaffold. The quantitative measurement of scaffold thickness showed a significant thinning across all cancer models (Fig. 2 d), mirroring the morphological contraction seen in the histological samples (Fig. 2 a). Finally, the relative total cell counts for the cancer models exhibited a decreasing trend as the neutron dose increased (Fig. 2 e). 3. Comparative validation of cell counting methodologies in 3D scaffolds Figure 3 illustrates the differences in cell counts obtained using three distinct methodologies across the tested cells lines. Dose–response analyses revealed that total cell numbers derived from histological assessment (red circles) and live cell counts following collagenase dissociation (blue circles) exhibited concordant and progressively decreasing trends with increasing radiation dose. This concordance was supported by positive Pearson correlation coefficients, most prominently in HUVEC (Fig. 3 c; r = 0.69, P = 0.197) and MG-63 (Fig. 3 f r = 0.86, P = 0.063). Although similar trends were observed in NOF and HSC-4, these did not reach statistical significance (r = 0.65 and r = 0.64, respectively). In contrast, total cell counts derived from enzymatic digestion (red circles) diverged substantially from the other two methodologies. A strong negative correlation was observed in NOF ( Fig. 3 a; r = − 0.89, P = 0.041), indicating an inverse relationship between automated counts and histological measurements. Comparable inverse trends were identified in MG-63 (Fig. 3 f; r = − 0.64, P = 0.241) and 2–3 (Fig. 3 d; r = − 0.58, P = 0.310), whereas the correlation was negligible in CAF (Fig. 3 b; r = − 0.20, P = 0.743). The robustness of 3D cell quantification was further supported by the stability of live cell size distributions across the dose range ( Supplementary Figs. 1d, f and 2d, f ). Discussion RBE remains a central yet incompletely resolved parameter in radiobiology, governing the balance between therapeutic efficacy and normal tissue safety 1 , 7 . A major barrier to its accurate estimation lies in the continued reliance on clonogenic assays, which, despite their status as the conventional gold standard, are fundamentally unsuitable for primary normal cells 13 – 15 . Unlike immortalized cancer cell lines, primary fibroblasts and endothelial cells lack sufficient proliferative capacity to form discrete colonies, thereby precluding reliable RBE quantification using traditional methodologies 16 , 18 . This methodological constraint has broad implications. There is an urgent need for alternative models to reliably estimate RBE of healthy tissues, a factor of crucial importance for setting occupational exposure limits in nuclear facilities 5 – 7 and assessing risks for cosmic radiation exposure during space missions 4 . This methodological gap is equally critical in the clinical optimization of BNCT 12 , where treatment protocols are primarily governed by the tolerance thresholds of healthy tissues rather than solely by the dose delivered to the tumor 21 , 22 . Our findings demonstrate that culture dimensionality fundamentally reshapes radiobiological responses. The 2D monolayer systems consistently overestimate neutron-induced cytotoxicity, as evidenced by steep dose response relationships across both normal and cancer cells (Fig. 1 ). For instance, the pronounced radiosensitivity of HUVEC in 2D, where survival fractions decline to approximately 0.1 at doses as low as 2 Gy stands in clear contrast to clinical observations 23 , in which vascular injury typically manifests at substantially higher dose levels (Fig. 1 a). Similarly, the exaggerated sensitivity of cancer cells in 2D would imply that neutron irradiation alone is sufficient for tumour eradication, contradicting the established requirement for boron-mediated dose amplification in BNCT 24 . In contrast, 3D tissue-mimetic models provide a more physiologically relevant representation of radiation response (Fig. 1 e-h ) . Across all examined cell populations, survival fractions remained above 0.1 even at doses up to 25 Gy, reflecting a degree of radioresistance that more closely aligns with clinical tolerance thresholds. Notably, patient-derived fibroblast populations (NOF and CAF) exhibited remarkable stability across both dimensional contexts, suggesting that stromal components may serve as intrinsic determinants of tissue resilience. The concordance between these experimental observations and the known clinical tolerance of oral mucosa in BNCT supports the validity of our model and underscores the capacity of 3D systems to recapitulate human tissue responses 22 – 26 . Moreover, the ability of patient-derived NOF models to reproduce clinically relevant dose response behaviour indicates that our experimental platform faithfully captures key features of human stromal biology. Consequently, the 3D scaffold-based environment provides a verisimilar framework for assessing the biological effectiveness of thermal neutrons 21 , 27 . Importantly, our findings extend beyond cell survival to encompass structural and microenvironmental responses 28 , 29 . Thermal neutron irradiation induced dose-dependent alterations in ECM integrity, evidenced by progressive scaffold thinning (Fig. 3 ). This phenomenon likely reflects localized energy deposition from nitrogen capture reactions, in which high-LET protons disrupt molecular bonds within collagen and polymer networks. These observations support a broader conceptualization of neutron-induced damage as a multi-scale process, integrating molecular, cellular, and tissue-level effects 28 – 30 . From a methodological perspective, the integration of complementary quantification strategies strengthens the robustness of our findings. By combining enzymatic dissociation-based survival analysis with automated histological image quantification, and validating consistency through Pearson correlation analysis, we establish a reproducible framework for analysing complex 3D systems ( Fig. 3 ) . This multi-modal approach mitigates the limitations inherent to each individual method and enhances confidence in the observed biological trends. Although the current model is characterized by relatively low cellular density and a high matrix-to-cell ratio, these features highlight an important conceptual shift. Rather than prioritizing clonogenic expansion, 3D systems enable assessment of tissue-level integrity, which is particularly relevant for non-clonogenic cell populations such as fibroblasts and endothelial cells. In this context, the apparent limitation of reduced colony formation becomes a strength, allowing evaluation of radiation effects in a framework that more closely reflects in vivo tissue organization. Taken together, our findings support a redefinition of neutron radiobiology as a systems-level discipline, in which biological effectiveness emerges from the interplay between cellular damage, tissue architecture, and microenvironmental dynamics. By demonstrating that 3D models provide a more accurate and clinically relevant platform for RBE estimation, this work contributes to the development of next-generation radiobiological frameworks that may ultimately inform safer and more precise neutron-based therapies. Conclusions Our study establishes three-dimensional tissue models as a clinically relevant platform for redefining RBE in neutron irradiation, addressing a critical gap in the assessment of normal tissue toxicity. By capturing multi-scale biological responses beyond clonogenic survival, this approach enables more accurate risk stratification and dose optimization. These advances provide a foundation for safer implementation and broader clinical adoption of neutron-based therapies, including BNCT. Materials and methods Cell lines and culture conditions The following cell lines were employed: human oral squamous cell carcinoma (OSCC) lines HSC-3 (JCRB0623, JCRB) and HSC-4 (JCRB0624, JCRB), the human osteosarcoma line MG-63 (IFO50108 JCRB), and human umbilical vein endothelial cells (HUVEC). Additionally, patient-derived normal oral fibroblasts (NOF) and cancer-associated fibroblasts (CAF) were provided by Niigata University (Ethical Approval #2022 − 0300). NOF and CAF were isolated from cancer-negative and cancer-positive sites of the same patient, respectively, as previously described 18 , 21 , and used between passages 1 and 4. HUVEC were maintained in KBM medium (KBM VEC-1 Basal Medium, Kohjin Bio, cod. 16030110) according to the manufacturer’s instructions. All other cell types were cultured in Alpha Modified Eagle Medium (α-MEM; Nacalai Tesque Inc., Kyoto, Japan) supplemented with 10% heat-inactivated fetal bovine serum (FBS; Corning, NY, USA) and 1% penicillin/streptomycin (10,000 U/mL and 10,000 µg/mL; Nacalai Tesque Inc.). All cultures were maintained in a humidified atmosphere at 37°C with 5% CO 2 . 2D and 3D cell culture For 2D experiments, cells were seeded at a density of 2x10 4 cells/well in 12-well plates (Thermo Fisher Scientific) with 2 mL of medium for well (Fig. 4 a ) . After 48 hours, prior to irradiation, the culture medium was aspirated from the plates. Following the exposure, the samples were immediately replaced with fresh culture medium. For 3D models, a cold-prepared extracellular matrix was used, consisting of 7 parts of cell matrix (Nitta Gelatin, Japan), 2 parts 5× DME (Nitta Gelatin, Japan), and 1 part of reconstruction buffer (Nitta Gelatin, Japan). All procedures were performed on ice to prevent premature polymerization. Cells were suspended in the matrix at a final concentration of 6 x10 5 cells/mL. A 500 µL volume of the cell–matrix suspension was seeded into each well of a 24-well plate (Thermo Fisher Scientific) and incubated at 37°C for 30 minutes to allow gelation (Fig. 4 a ) . After polymerization, 1 mL of culture medium was added. After 48 hours, prior to irradiation, the culture medium was aspirated from the plates. Following the exposure, the samples were immediately replaced with fresh culture medium. Following neutron irradiation, both 2D monolayer cultures and 3D constructs were maintained in humified atmosphere at 37°C with 5% CO 2 for a period of 72 hours prior to further experimental procedures ( Fig. 4 b ). Irradiation Protocol Neutron irradiation was performed at the Kyoto University Research Reactor (KUR). Both 2D monolayers and 3D constructs were exposed to reactor power levels of either 1 MW or 5 MW to achieve the target absorbed doses (Fig. 4 a). Specifically, doses of 2.5 ± 0.5 Gy and 5.3 ± 0.5 Gy were delivered at 1 MW with exposure times of 55 and 150 minutes, respectively. Higher doses of 13.2 ± 1.5 Gy and 25.8 ± 1.9 Gy were obtained by operating the reactor at 5 MW for 60 and 120 minutes, respectively. To verify the accuracy of the delivered neutron fluence, gold foil dosimeters and thermoluminescent dosimeters (TLD) were placed directly on the culture plates during irradiation 20 . Viability Analysis 2D cultures cells were detached using 0.025% trypsin/EDTA (NACALAI TESQUE Inc., Kyoto, Japan) and counted via trypan blue exclusion (Invitrogen, USA). The matrix of 3D scaffold was digested using a collagenase solution (0.1 g of collagenase and 14.7 mg of CaCl 2 in 50 mL H 2 O) at 37°C under gentle agitation for 60 minutes. Following centrifugation and resuspension cells were counted via trypan blue exclusion (1:1 dilution). Total cell numbers, live cell numbers and mean diameter were assessed using an automated cell counting system (Countess II FL, Invitrogen, USA). Histology analysis 3D cell culture models were fixed in 4% paraformaldehyde (PFA), embedded in paraffin, and sectioned at 5 µm. Sections were stained with Hematoxylin and Eosin (H&E) and imaged using an all-in-one fluorescence microscope (BZ-X800, Keyence, Osaka, Japan). Quantitative analysis was conducted using ImageJ Fiji (version 1.54f; National Institutes of Health, Bethesda, MD, USA). Regions of interest (ROIs) were manually defined, and tissue segmentation was performed via grayscale thresholding to generate binary masks. Total tissue area, nuclei count (via particle analysis), and apparent tissue thickness (vertical height of the bounding box) were calculated from calibrated images. Statistical Analysis All experimental procedures were performed using three to four independent samples per condition. Statistical evaluations were performed using GraphPad Prism 8 (GraphPad Software, San Diego, CA, USA). Data are expressed as mean±standard deviation (SD) and, where applicable, normalized to the corresponding 0 Gy control. To evaluate the effects of radiation dose, cell line, and culture system (2D vs. 3D), two-way analysis of variance (ANOVA) was employed. Multiple comparisons were conducted using Tukey’s post-hoc test to assess differences among multiple groups, while Sidak’s post-hoc test was used for comparisons between specific conditions (e.g., 2D vs. 3D). For histological and counting data where single factors were analysed, one-way ANOVA was applied. The consistency between different cell counting methodologies was evaluated using the Pearson correlation coefficient (r). Statistical significance was defined as P < 0.05, with levels indicated as *p < 0,05, **p < 0.001, ***p < 0.001 and ****p < 0.0001. Declarations Funding Declaration This work was supported by JSPS KAKENHI Grant Number 23K11918. Author Contribution K. Igawa conceived the study, S.L. and I.Y. assisted by K.Igawa, K.Izumi and K.S. performed 2D and 3D cell culture experiments. Y.S. and N.K.provided thermal neturon source and performed the dose calculation. K.Igawa performed the neutron irradiation in 2D and 3D cell culture. S.L and I.Y. conducted the violability analysis and S.L. performed the histological analysis. S.L. and K.I wrote the manuscript with input from all authors. All authors discussed the results and commented on the manuscript. Acknowledgement We would like to thank all the staff at the Institute of Central Research Laboratory, Okayama University Medical School, for their assistance with the histological analysis and the Institute for Integrated Radiation and Nuclear Science, Kyoto University, for their technical assistance during the irradiation. Data Availability All data supporting the findings of this study are included in this published article and its Supplementary Information files. The datasets are also publicly available from the Okayama University Scientific Achievement Repository, ousar.lib.okayama-u.ac.jp. Additional raw data are available from the corresponding author upon reasonable request. References Report, I. C. R. U. 46, Photon, Electron, Proton and Neutron Interaction Data for Body Tissues – ICRU. https://www.icru.org/report/photon-electron-proton-and-neutron-interaction-data-for-body-tissues-report-46/ Barth, R. F., Coderre, J. A., Vicente, M. G. H. & Blue, T. E. Boron neutron capture therapy of cancer: current status and future prospects. Clin. Cancer Res. 11 , 3987–4002 (2005). Mentana, A. et al. Mapping neutron biological effectiveness for DNA damage induction as a function of incident energy and depth in a human sized phantom. Scientific Reports 2025 15:1 15, 2209- (2025). Li, X. et al. Measurement of electrons from albedo neutron decay and neutron density in near-Earth space. Nature 552 , 382–385 (2017). Ferrarini, M., EXPOSURE RISK FOR WORKERS & IN AN HADRONTHERAPY CENTRE AND COLLECTIVE AND INDIVIDUAL PROTECTION MEASURES. G Ital. Med. Lav Ergon. 42 , 257–261 (2025). Azhgirey, I. L. & NEUTRON MONITORS FOR HIGH ENERGY ACCELERATORS.. https://doi.org/10.18429/JACoW-RUPAC2018-TUPSA38 (2018). 10.18429/JACoW-RUPAC2018-TUPSA38 Icrp & Annals of the ICRP Published on behalf of the International Commission on Radiological Protection.. https://doi.org/10.1177/ANIB_37_2-4 doi:10.1177/ANIB_37_2-4. Suzuki, M. Boron neutron capture therapy (BNCT): a unique role in radiotherapy with a view to entering the accelerator-based BNCT era. Int. J. Clin. Oncol. 25 , 43–50 (2020). Coderre, J. A. & Morris, G. M. The Radiation Biology of Boron Neutron Capture Therapy. Radiat. Res. 151 , 1 (1999). Goodhead, D. T. Initial events in the cellular effects of ionizing radiations: clustered damage in DNA. INT. J. RADIAT. BIOL. 65 , 7–17 (1994). Nikjoo, H., O’Neill, P., Terrissol, M. & Goodhead, D. T. Modelling of radiation-induced DNA damage: the early physical and chemical event. Int. J. Radiat. Biol. 66 , 453–457 (1994). Moss, R. L. Critical review, with an optimistic outlook, on Boron Neutron Capture Therapy (BNCT). Appl. Radiat. Isot. 88 , 2–11 (2014). Kapałczyńska, M. et al. 2D and 3D cell cultures – a comparison of different types of cancer cell cultures. Arch. Med. Sci. 14 , 910 (2016). Santini, M. T., Rainaldi, G. & Indovina, P. L. Multicellular tumour spheroids in radiation biology. Int. J. Radiat. Biol. 75 , 787–799 (1999). Hirschhaeuser, F. et al. Multicellular tumor spheroids: An underestimated tool is catching up again. J. Biotechnol. 148 , 3–15 (2010). Antonelli, F. 3D Cell Models in Radiobiology: Improving the Predictive Value of In Vitro Research. Int. J. Mol. Sci. 24 , 10620 (2023). Sharma, K., Dey, S., Karmakar, R. & Rengan, A. K. A comprehensive review of 3D cancer models for drug screening and translational research. Cancer Innov. 3 , e102 (2023). Aizawa, Y. et al. Development and Characterization of a Three-Dimensional Organotypic In Vitro Oral Cancer Model with Four Co-Cultured Cell Types, Including Patient-Derived Cancer-Associated Fibroblasts. Biomedicines 12, (2024). Charalampopoulou, A. et al. The rise of 3D spheroids in radiobiology for assessing tumour radioresistance. Acta Oncol. 65 , 46–58 (2026). Sakurai, Y. & Kobayashi, T. The medical-irradiation characteristics for neutron capture therapy at the Heavy Water Neutron Irradiation Facility of Kyoto University Research Reactor. Med. Phys. 29 , 2328–2337 (2002). Yamamoto, I. et al. The Early Response After Radiation Therapy on Three-Dimensional Oral Cancer Model Using Patient-Derived Cancer-Associated Fibroblasts. Int. J. Translational Med. 2025 . 5 (1), 12 (2025). Fukuda, H. Response of normal tissues to boron neutron capture therapy (BNCT) with10 b-borocaptate sodium (BSH) and 10 b-paraboronophenylalanine (BPA). Cells 10 (11), 2883 (2021). Park, H. J., Griffin, R. J., Hui, S., Levitt, S. H. & Song, C. W. Radiation-induced vascular damage in tumors: implications of vascular damage in ablative hypofractionated radiotherapy (SBRT and SRS). Radiat. Res. 177 , 311–327 (2012). Hirose, K., Sato, M., Ichise, K. & Aoki, M. Dose Rate Effect on Cell Survival in BNCT. Curr. Issues Mol. Biol. 45 , 6986–6994 (2023). Raitanen, J. et al. Comparison of radiation response between 2D and 3D cell culture models of different human cancer cell lines. Cells 12 , 360 (2023). Kato, I. et al. Effectiveness of boron neutron capture therapy for recurrent head and neck malignancies. Appl. Radiat. Isot. 67 , 7–8 (2009). Igawa, K., Izumi, K. & Sakurai, Y. Development of the Follow-Up Human 3D Oral Cancer Model in Cancer Treatment. BioTech. 2023 . 12 (2), 35 (2023). Yu, L. S. et al. Tissue architecture influences the biological effectiveness of boron neutron capture therapy in in vitro/in silico three-dimensional self-assembly cell models of pancreatic cancers. Cancers (Basel) . 13 , 4058 (2021). Barcellos-Hoff, M. H., Park, C. & Wright, E. G. Radiation and the microenvironment - tumorigenesis and therapy. Nat. Rev. Cancer . 5 , 867–875 (2005). Krisnawan, V. E., Stanley, J. A., Schwarz, J. K. & Denardo, D. G. Tumor Microenvironment as a Regulator of Radiation Therapy: New Insights into Stromal-Mediated Radioresistance. Cancers (Basel) . 12 , 1–25 (2020). Additional Declarations No competing interests reported. Supplementary Files Supplementary20260408.pdf Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 19 May, 2026 Reviews received at journal 19 May, 2026 Reviewers agreed at journal 21 Apr, 2026 Reviewers agreed at journal 21 Apr, 2026 Reviewers agreed at journal 21 Apr, 2026 Reviewers invited by journal 21 Apr, 2026 Editor assigned by journal 18 Apr, 2026 Editor invited by journal 17 Apr, 2026 Submission checks completed at journal 14 Apr, 2026 First submitted to journal 14 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9354079","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":627374702,"identity":"0eeccbc2-b92f-46e6-a832-1fda8921d5f8","order_by":0,"name":"Susanna Leva","email":"","orcid":"","institution":"National Centre of Oncological Hadrontherapy","correspondingAuthor":false,"prefix":"","firstName":"Susanna","middleName":"","lastName":"Leva","suffix":""},{"id":627374703,"identity":"e569ced0-8046-44f7-92ff-3d9e441422ec","order_by":1,"name":"Kazuyo Igawa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABHklEQVRIiWNgGAWjYBACNjB5AEwyPoAyYACVh00LswFRWpDl2CTwKoIBPv7FzyR+nLGzN7iRfKziwxm7xP5phx8w8zDYyTMwnsVqApvEMzPJnhvJzAY30tJuzriRnDjjdpoBUEuyYQPDuQTsWg6Y3eD5wMxmcCPH7DaQkdhwO8H8Nw8DM1D5GQPsWo5/u/nnQz0PSEsxz4f6xPm30z8AbanHrYW/B2j4jcMSIC3MQEbihts5IIcdxmMLT/lvmTPHDSTPPEuWnHHmuPHG2zkFjHMMjhu24fCLfP/xzYZvjlXb8x1PPvjhw7Fq2Xm30zcwvKmolueXwB5iDBIwkwQgDMcGMGUAcsAZrDoY+A+gMuyRpHqwaxkFo2AUjIKRBgDHb2leRe74nQAAAABJRU5ErkJggg==","orcid":"","institution":"Okayama University","correspondingAuthor":true,"prefix":"","firstName":"Kazuyo","middleName":"","lastName":"Igawa","suffix":""},{"id":627374704,"identity":"b05374bf-aec8-421a-a812-2f1ed4b86c90","order_by":2,"name":"Izumi Yamamoto","email":"","orcid":"","institution":"Okayama University","correspondingAuthor":false,"prefix":"","firstName":"Izumi","middleName":"","lastName":"Yamamoto","suffix":""},{"id":627374705,"identity":"9bb8efd7-0040-4b96-9bd2-a03bfc1ccd45","order_by":3,"name":"Yoshinori Sakurai","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Yoshinori","middleName":"","lastName":"Sakurai","suffix":""},{"id":627374706,"identity":"421c742a-cf73-4e9d-8ed3-79182468d5c4","order_by":4,"name":"Natsuko Kondo","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Natsuko","middleName":"","lastName":"Kondo","suffix":""},{"id":627374707,"identity":"0ee21f67-06fe-47ff-8ddf-970e1d207cba","order_by":5,"name":"Kenji Izumi","email":"","orcid":"","institution":"Niigata University","correspondingAuthor":false,"prefix":"","firstName":"Kenji","middleName":"","lastName":"Izumi","suffix":""},{"id":627374708,"identity":"2e2957b5-1b6d-4e54-9987-4879a3de8a92","order_by":6,"name":"Kae Sato","email":"","orcid":"","institution":"Japan Women's University","correspondingAuthor":false,"prefix":"","firstName":"Kae","middleName":"","lastName":"Sato","suffix":""}],"badges":[],"createdAt":"2026-04-08 08:39:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9354079/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9354079/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108491033,"identity":"7386199e-5d6d-4982-b556-2e4a4a0c5c01","added_by":"auto","created_at":"2026-05-05 09:51:24","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":95681,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparative radiobiological response of 2D and 3D cultures.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a–b) \u003c/strong\u003eSurvival fractions of stromal \u003cstrong\u003e(a) \u003c/strong\u003eand cancer \u003cstrong\u003e(b) \u003c/strong\u003ecell lines in 2D monocultures across a neutron dose range (0–25.8 Gy). \u003cstrong\u003e(c–d) \u003c/strong\u003eSurvival fractions of stromal \u003cstrong\u003e(c) \u003c/strong\u003eand cancer \u003cstrong\u003e(d) \u003c/strong\u003ecell lines in 3D scaffolds. \u003cstrong\u003e(e–h) \u003c/strong\u003eDirect comparison between 2D (red bars) and 3D (green bars) survival fractions at 2.5 Gy \u003cstrong\u003e(e)\u003c/strong\u003e, 5.3 Gy \u003cstrong\u003e(f)\u003c/strong\u003e, 13.2 Gy \u003cstrong\u003e(g)\u003c/strong\u003e, and 25.8 Gy \u003cstrong\u003e(h)\u003c/strong\u003e. All values are shown on a semi-logarithmic scale and represent the mean ± standard deviation (SD). Statistical analysis for panels \u003cstrong\u003e(a–d)\u003c/strong\u003ewas performed using Two-way ANOVA followed by Tukey’s multiple comparisons post-hoc test. Statistical analysis for panels (e–h) was performed using Two-way ANOVA followed by Sidak’s multiple comparisons post-hoc test. *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9354079/v1/c6d115819b9c7bb6ad1f82e7.png"},{"id":108491170,"identity":"ad5376ae-85ee-4f18-aa45-420011013ed8","added_by":"auto","created_at":"2026-05-05 09:52:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":264379,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eH\u0026amp;E representative images and histological analysis of 3D constructs.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a)\u003c/strong\u003e Representative histological sections of NOF, CAF, HUVEC, HSC-3, HSC-4 and MG-63 3D constructs stained with haematoxylin and eosin (H\u0026amp;E) at doses from 0 to 25.8 Gy (scale bar= 100 µm). \u003cstrong\u003e(b)\u003c/strong\u003e Quantitative analysis of NOF, CAF, and HUVEC constructs thickness (scale bar=100 um) as a function of neutron dose. \u003cstrong\u003e(c)\u003c/strong\u003e Total nuclear count per section of NOF, CAF and HUVEC scaffolds derived from quantitative histological analysis, normalized to 0 Gy controls. \u003cstrong\u003e(d)\u003c/strong\u003eQuantitative analysis of HSC-3, HSC-4 and MG-63 constructs thickness (scale bar=100 um) as a function of neutron dose. \u003cstrong\u003e(e)\u003c/strong\u003eTotal nuclear count per section of HSC-3, HSC-4 and MG-63 scaffolds derived from quantitative histological analysis, normalized to 0 Gy controls. All data are shown as mean ± SD.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9354079/v1/f11c1ba899344bb39ce9c280.png"},{"id":108220073,"identity":"491fdb0b-6fa6-4aa8-8d89-01d836a87d0d","added_by":"auto","created_at":"2026-04-30 15:16:17","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":75515,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMethodological evaluation for cell counting in 3D scaffolds.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a-f) \u003c/strong\u003eDose-response trends comparing Total Histology (red), Total Cell Count via Collagenase (green), and Live Cell Count via Collagenase (blue) for: \u003cstrong\u003e(a) \u003c/strong\u003eNOF, \u003cstrong\u003e(b) \u003c/strong\u003eCAF, \u003cstrong\u003e(c) \u003c/strong\u003eHUVEC, \u003cstrong\u003e(d) \u003c/strong\u003eHSC-3, \u003cstrong\u003e(e) \u003c/strong\u003eHSC-4, and \u003cstrong\u003e(f) \u003c/strong\u003eMG-632. All data are shown as mean ± SD normalized to respective 0 Gy. Statistical validation was performed using a Pearson correlation matrix for each cell line to assess inter-methodological consistency.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9354079/v1/c5b46a2b30a021d5fad67bd9.png"},{"id":108220075,"identity":"28fbc980-4929-48b0-b3f5-21291d104b83","added_by":"auto","created_at":"2026-04-30 15:16:17","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":83553,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExperimental set-up and workflow.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a)\u003c/strong\u003eThe schematic summarizes the sequential procedures from model establishment, irradiation and final aims.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(b)\u003c/strong\u003e Comparison of the culture dimensionality configurations: 2D model (left) and 3D model (right).\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9354079/v1/afa792ca4a558a98d04448e8.png"},{"id":108976596,"identity":"1cfd59b7-9e3a-4c51-a4e8-a5e5be9f012f","added_by":"auto","created_at":"2026-05-11 11:25:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":662896,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9354079/v1/da1bd41e-77d2-4642-bd1a-21127375a721.pdf"},{"id":108220071,"identity":"a2f96f1a-5288-4e27-b903-91fa83338b92","added_by":"auto","created_at":"2026-04-30 15:16:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":508359,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary20260408.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9354079/v1/0babbeb811faf1b617c89dfc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Bridging the translational gap in radiotherapy: a human three-dimensional cell culture for evaluating neutron biological effects","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNeutron radiobiology represents a distinctive paradigm within radiation science, defined by the unique physical interactions of neutrons with biological matter and the complex patterns of energy deposition that ensue \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Unlike photons or charged particles, which predominantly interact with atomic electrons, neutrons are indirectly ionizing and deposit energy through nuclear interactions, generating cascades of high-linear energy transfer (LET) secondary particles \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. These processes give rise to densely clustered DNA damage, challenging canonical models of radiation response and repair.\u003c/p\u003e \u003cp\u003eThe biological consequences of neutron exposure span multiple domains, from space radiation biology, where secondary neutrons contribute substantially to astronaut risk \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, to radiation protection in high-energy physics environments \u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. In oncology, these unique properties are harnessed therapeutically in boron neutron capture therapy (BNCT), a modality that exploits neutron capture reactions to achieve highly localized, cell-selective cytotoxicity \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHowever, a fundamental yet underappreciated aspect of neutron radiobiology is the intrinsic biological activity of thermal neutrons in native tissue environments, independent of exogenous boron delivery \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Thermal neutrons, despite their low kinetic energy (~\u0026thinsp;0.025 eV), induce biologically significant effects through nuclear capture reactions with endogenous elements, particularly nitrogen and hydrogen. The \u0026sup1;⁴N(n,p)\u0026sup1;⁴C reaction generates high-LET protons, whereas \u0026sup1;H(n,γ)\u0026sup2;H produces low-LET gamma radiation, together shaping a composite radiation field within tissues \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis duality underscores a key conceptual challenge: the biological effectiveness of neutrons cannot be fully understood through conventional radiobiological frameworks that are largely derived from photon-based systems \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Instead, neutron-induced damage reflects a multi-scale phenomenon, encompassing not only direct DNA damage but also perturbations of tissue architecture and microenvironmental integrity \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Consequently, accurate estimation of relative biological effectiveness (RBE) remains a central and unresolved issue in both radiation protection\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e and clinical translation \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHistorically, the quantification of RBE has been conducted using two-dimensional (2D) monolayer cultures and clonogenic survival assays. Despite the fact that these approaches have yielded foundational insights, they are intrinsically reductionist and fail to capture the spatial, structural, and biochemical complexity of living tissues \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Notably, these models fail to incorporate the significance of cell-to-cell interactions and the influence of the extracellular matrix (ECM) on radiosensitivity. Furthermore, they do not consider the oxygen, nutrient, and signalling molecule gradients that have been identified as critical regulators of radiosensitivity \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe limitations of 2D systems have catalysed a paradigm shift toward three-dimensional (3D) tissue models, including spheroids and scaffold-based constructs, which more faithfully recapitulate tissue organization and microenvironmental heterogeneity. These models reveal that radiosensitivity is not an intrinsic cellular property alone but is emergent from multicellular architecture and context-dependent signalling networks\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. As such, 3D systems offer a more physiologically relevant framework for interrogating neutron-induced biological effects and refining RBE estimation.\u003c/p\u003e \u003cp\u003eImportantly, this transition from 2D to 3D models reframes neutron radiobiology as a systems-level problem, in which radiation effects must be understood across multiple spatial and temporal scales from molecular damage to tissue-level dysfunction \u003csup\u003e\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Within this context, features such as extracellular matrix remodelling and microenvironmental disruption emerge as critical determinants of radiation response, extending beyond traditional endpoints based solely on clonogenic survival \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this study, we address these conceptual and methodological gaps by systematically comparing the effects of thermal neutron irradiation in 2D and 3D culture systems. Using controlled neutron exposures at the Kyoto University Research Reactor (KUR), we investigate how culture dimensionality shapes radiosensitivity and biological response across clinically relevant dose ranges. Furthermore, we integrate quantitative validation strategies to ensure robust assessment within complex 3D architectures.\u003c/p\u003e \u003cp\u003eBy bridging physical dosimetry with advanced tissue-mimetic modelling, this work contributes to the emerging framework of next-generation radiobiology, in which experimentally tractable yet physiologically relevant systems are leveraged to refine risk assessment and inform precision radiotherapy strategies.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003e1. Evaluation of radiobiological response in 2D and 3D models of stromal and cancer cells\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe evaluation of survival fractions across a neutron dose range of 0 to 25.8 Gy revealed a consistent dose-dependent reduction in viability for all cell lines tested in 2D monolayers (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, b). In the 2D stromal cell cultures, human umbilical vein endothelial cells (HUVEC) cells exhibited lower survival rates compared to patient-derived normal oral fibroblasts (NOF) and patient-derived cancer-associated fibroblasts (CAF), with a statistically significant difference emerging at 2.5 Gy (*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Similarly, the 2D cancer cell cultures showed a steady decrease in survival as the neutron dose increased, with lowly metastatic human oral squamous cell carcinoma (HSC-4) demonstrating higher radio sensitivity compared to the human osteosarcoma cells (MG-63) and highly metastatic human oral squamous cell carcinoma (HSC-3) at 2.5 Gy (**p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Complementary morphological characterization of 2D monolayers and detailed viability metrics, including live cell percentage and mean cell diameter, are provided (\u003cb\u003eSupplementary Fig.\u0026nbsp;1, 2\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eFor stromal cells cultured in a 3D model, the decrease in survival rate was attenuated with increasing neutron dose (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec, d). In this 3D stromal environment, no significant differences were observed among the cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). Furthermore, no apparent reduction in survival rate was observed in the 3D tumour model (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). Despite this overall stability specific significant differences were observed at low doses, particularly at 2.5 Gy (****p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and 5.3 Gy (*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), where HSC-4 showed a higher survival compared to HSC-3 and MG-63.\u003c/p\u003e \u003cp\u003eThe direct comparison between 2D and 3D cultures across the different neutron radiation doses (2.5, 5.3, 13.2, and 25.8 Gy) revealed a significant divergence in survival profiles for most cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee, h). At the dose of 2.5 Gy, a significant increase in radio resistance was observed in the 3D models for HSC-4 (****p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and HUVEC (**p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) compared to their 2D counterparts (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee). This lower response of the cells in 3D environment was further confirmed at 5.3 Gy, where the divergence reached maximum significance for HUVEC, and HSC-3 (****p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), while HSC-4 and MG-63 also showed a significant difference (**p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef). At 13.2 Gy, the response reached a peak of divergence, with all cancer and stromal lines, excluding NOF and CAF, showing the maximum level of statistical significance (****p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eg). At 25.8 Gy, the statistical profile shifted: while a maximum divergence was maintained for HSC-3, MG-63, and HUVEC (****p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), the difference between 2D and 3D survival for HSC-4, though still significant, was characterized by a lower level of significance (**p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eh).\u003c/p\u003e \u003cp\u003eIn contrast, the NOF and CAF lines demonstrated a remarkably stable response regardless of the culture system. Across the entire neutron dose range, no significant differences were observed between the 2D and 3D configurations for these two patient delivered cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee, h). Both NOF and CAF consistently exhibited an intrinsic radio resistance, with a low reduction in viability that remained independent of the culture model.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2. Histological assessment of 3D scaffolds in cancer and stromal cell models\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe structural impact of neutron irradiation on the 3D models was evaluated by integrating qualitative histological observations with a quantitative approach to measure tissue parameters. As demonstrated in the representative sections of the 3D cancer scaffolds, there is a visible and progressive contraction of the scaffold matrix as the neutron dose increases from 0 to 25.8 Gy (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). For the stromal models (NOF, CAF, HUVEC), this structural response was confirmed by the quantitative analysis of scaffold thickness, where a dose-dependent thinning is recorded for all stromal lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Parallel to the matrix contraction, the nuclear count analysis indicated that the total number of stromal cells within the 3D environment underwent a slight reduction in a dose dependent manner (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). A similar pattern was observed for the 3D cancer scaffold. The quantitative measurement of scaffold thickness showed a significant thinning across all cancer models (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed), mirroring the morphological contraction seen in the histological samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Finally, the relative total cell counts for the cancer models exhibited a decreasing trend as the neutron dose increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee).\u003c/p\u003e \u003cp\u003e \u003cb\u003e3. Comparative validation of cell counting methodologies in 3D scaffolds\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates the differences in cell counts obtained using three distinct methodologies across the tested cells lines. Dose\u0026ndash;response analyses revealed that total cell numbers derived from histological assessment (red circles) and live cell counts following collagenase dissociation (blue circles) exhibited concordant and progressively decreasing trends with increasing radiation dose. This concordance was supported by positive Pearson correlation coefficients, most prominently in HUVEC (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec; r\u0026thinsp;=\u0026thinsp;0.69, P\u0026thinsp;=\u0026thinsp;0.197) and MG-63 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef r\u0026thinsp;=\u0026thinsp;0.86, P\u0026thinsp;=\u0026thinsp;0.063). Although similar trends were observed in NOF and HSC-4, these did not reach statistical significance (r\u0026thinsp;=\u0026thinsp;0.65 and r\u0026thinsp;=\u0026thinsp;0.64, respectively). In contrast, total cell counts derived from enzymatic digestion (red circles) diverged substantially from the other two methodologies. A strong negative correlation was observed in NOF \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea; r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.89, P\u0026thinsp;=\u0026thinsp;0.041), indicating an inverse relationship between automated counts and histological measurements. Comparable inverse trends were identified in MG-63 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef; r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.64, P\u0026thinsp;=\u0026thinsp;0.241) and 2\u0026ndash;3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed; r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.58, P\u0026thinsp;=\u0026thinsp;0.310), whereas the correlation was negligible in CAF (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb; r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.20, P\u0026thinsp;=\u0026thinsp;0.743). The robustness of 3D cell quantification was further supported by the stability of live cell size distributions across the dose range (\u003cb\u003eSupplementary Figs.\u0026nbsp;1d, f and 2d, f\u003c/b\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eRBE remains a central yet incompletely resolved parameter in radiobiology, governing the balance between therapeutic efficacy and normal tissue safety \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. A major barrier to its accurate estimation lies in the continued reliance on clonogenic assays, which, despite their status as the conventional gold standard, are fundamentally unsuitable for primary normal cells\u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Unlike immortalized cancer cell lines, primary fibroblasts and endothelial cells lack sufficient proliferative capacity to form discrete colonies, thereby precluding reliable RBE quantification using traditional methodologies \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis methodological constraint has broad implications. There is an urgent need for alternative models to reliably estimate RBE of healthy tissues, a factor of crucial importance for setting occupational exposure limits in nuclear facilities\u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e and assessing risks for cosmic radiation exposure during space missions \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. This methodological gap is equally critical in the clinical optimization of BNCT \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, where treatment protocols are primarily governed by the tolerance thresholds of healthy tissues rather than solely by the dose delivered to the tumor\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur findings demonstrate that culture dimensionality fundamentally reshapes radiobiological responses. The 2D monolayer systems consistently overestimate neutron-induced cytotoxicity, as evidenced by steep dose response relationships across both normal and cancer cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). For instance, the pronounced radiosensitivity of HUVEC in 2D, where survival fractions decline to approximately 0.1 at doses as low as 2 Gy stands in clear contrast to clinical observations \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, in which vascular injury typically manifests at substantially higher dose levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Similarly, the exaggerated sensitivity of cancer cells in 2D would imply that neutron irradiation alone is sufficient for tumour eradication, contradicting the established requirement for boron-mediated dose amplification in BNCT \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn contrast, 3D tissue-mimetic models provide a more physiologically relevant representation of radiation response (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee-h\u003cb\u003e)\u003c/b\u003e. Across all examined cell populations, survival fractions remained above 0.1 even at doses up to 25 Gy, reflecting a degree of radioresistance that more closely aligns with clinical tolerance thresholds. Notably, patient-derived fibroblast populations (NOF and CAF) exhibited remarkable stability across both dimensional contexts, suggesting that stromal components may serve as intrinsic determinants of tissue resilience. The concordance between these experimental observations and the known clinical tolerance of oral mucosa in BNCT supports the validity of our model and underscores the capacity of 3D systems to recapitulate human tissue responses \u003csup\u003e\u003cspan additionalcitationids=\"CR23 CR24 CR25\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Moreover, the ability of patient-derived NOF models to reproduce clinically relevant dose response behaviour indicates that our experimental platform faithfully captures key features of human stromal biology. Consequently, the 3D scaffold-based environment provides a verisimilar framework for assessing the biological effectiveness of thermal neutrons \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eImportantly, our findings extend beyond cell survival to encompass structural and microenvironmental responses \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Thermal neutron irradiation induced dose-dependent alterations in ECM integrity, evidenced by progressive scaffold thinning (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This phenomenon likely reflects localized energy deposition from nitrogen capture reactions, in which high-LET protons disrupt molecular bonds within collagen and polymer networks. These observations support a broader conceptualization of neutron-induced damage as a multi-scale process, integrating molecular, cellular, and tissue-level effects \u003csup\u003e\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFrom a methodological perspective, the integration of complementary quantification strategies strengthens the robustness of our findings. By combining enzymatic dissociation-based survival analysis with automated histological image quantification, and validating consistency through Pearson correlation analysis, we establish a reproducible framework for analysing complex 3D systems \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. This multi-modal approach mitigates the limitations inherent to each individual method and enhances confidence in the observed biological trends.\u003c/p\u003e \u003cp\u003eAlthough the current model is characterized by relatively low cellular density and a high matrix-to-cell ratio, these features highlight an important conceptual shift. Rather than prioritizing clonogenic expansion, 3D systems enable assessment of tissue-level integrity, which is particularly relevant for non-clonogenic cell populations such as fibroblasts and endothelial cells. In this context, the apparent limitation of reduced colony formation becomes a strength, allowing evaluation of radiation effects in a framework that more closely reflects in vivo tissue organization.\u003c/p\u003e \u003cp\u003eTaken together, our findings support a redefinition of neutron radiobiology as a systems-level discipline, in which biological effectiveness emerges from the interplay between cellular damage, tissue architecture, and microenvironmental dynamics. By demonstrating that 3D models provide a more accurate and clinically relevant platform for RBE estimation, this work contributes to the development of next-generation radiobiological frameworks that may ultimately inform safer and more precise neutron-based therapies.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur study establishes three-dimensional tissue models as a clinically relevant platform for redefining RBE in neutron irradiation, addressing a critical gap in the assessment of normal tissue toxicity. By capturing multi-scale biological responses beyond clonogenic survival, this approach enables more accurate risk stratification and dose optimization. These advances provide a foundation for safer implementation and broader clinical adoption of neutron-based therapies, including BNCT.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eCell lines and culture conditions\u003c/h2\u003e \u003cp\u003eThe following cell lines were employed: human oral squamous cell carcinoma (OSCC) lines HSC-3 (JCRB0623, JCRB) and HSC-4 (JCRB0624, JCRB), the human osteosarcoma line MG-63 (IFO50108 JCRB), and human umbilical vein endothelial cells (HUVEC). Additionally, patient-derived normal oral fibroblasts (NOF) and cancer-associated fibroblasts (CAF) were provided by Niigata University (Ethical Approval #2022\u0026thinsp;\u0026minus;\u0026thinsp;0300). NOF and CAF were isolated from cancer-negative and cancer-positive sites of the same patient, respectively, as previously described \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, and used between passages 1 and 4.\u003c/p\u003e \u003cp\u003eHUVEC were maintained in KBM medium (KBM VEC-1 Basal Medium, Kohjin Bio, cod. 16030110) according to the manufacturer\u0026rsquo;s instructions. All other cell types were cultured in Alpha Modified Eagle Medium (α-MEM; Nacalai Tesque Inc., Kyoto, Japan) supplemented with 10% heat-inactivated fetal bovine serum (FBS; Corning, NY, USA) and 1% penicillin/streptomycin (10,000 U/mL and 10,000 \u0026micro;g/mL; Nacalai Tesque Inc.). All cultures were maintained in a humidified atmosphere at 37\u0026deg;C with 5% CO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2D and 3D cell culture\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFor 2D experiments, cells were seeded at a density of 2x10\u003csup\u003e4\u003c/sup\u003e cells/well in 12-well plates (Thermo Fisher Scientific) with 2 mL of medium for well (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea\u003cb\u003e)\u003c/b\u003e. After 48 hours, prior to irradiation, the culture medium was aspirated from the plates. Following the exposure, the samples were immediately replaced with fresh culture medium.\u003c/p\u003e \u003cp\u003eFor 3D models, a cold-prepared extracellular matrix was used, consisting of 7 parts of cell matrix (Nitta Gelatin, Japan), 2 parts 5\u0026times; DME (Nitta Gelatin, Japan), and 1 part of reconstruction buffer (Nitta Gelatin, Japan). All procedures were performed on ice to prevent premature polymerization. Cells were suspended in the matrix at a final concentration of 6 x10\u003csup\u003e5\u003c/sup\u003e cells/mL. A 500 \u0026micro;L volume of the cell\u0026ndash;matrix suspension was seeded into each well of a 24-well plate (Thermo Fisher Scientific) and incubated at 37\u0026deg;C for 30 minutes to allow gelation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea\u003cb\u003e)\u003c/b\u003e. After polymerization, 1 mL of culture medium was added. After 48 hours, prior to irradiation, the culture medium was aspirated from the plates. Following the exposure, the samples were immediately replaced with fresh culture medium.\u003c/p\u003e \u003cp\u003eFollowing neutron irradiation, both 2D monolayer cultures and 3D constructs were maintained in humified atmosphere at 37\u0026deg;C with 5% CO\u003csub\u003e2\u003c/sub\u003e for a period of 72 hours prior to further experimental procedures \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eIrradiation Protocol\u003c/h3\u003e\n\u003cp\u003eNeutron irradiation was performed at the Kyoto University Research Reactor (KUR). Both 2D monolayers and 3D constructs were exposed to reactor power levels of either 1 MW or 5 MW to achieve the target absorbed doses (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). Specifically, doses of 2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 Gy and 5.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 Gy were delivered at 1 MW with exposure times of 55 and 150 minutes, respectively. Higher doses of 13.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 Gy and 25.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9 Gy were obtained by operating the reactor at 5 MW for 60 and 120 minutes, respectively. To verify the accuracy of the delivered neutron fluence, gold foil dosimeters and thermoluminescent dosimeters (TLD) were placed directly on the culture plates during irradiation\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eViability Analysis\u003c/h2\u003e \u003cp\u003e2D cultures cells were detached using 0.025% trypsin/EDTA (NACALAI TESQUE Inc., Kyoto, Japan) and counted via trypan blue exclusion (Invitrogen, USA). The matrix of 3D scaffold was digested using a collagenase solution (0.1 g of collagenase and 14.7 mg of CaCl\u003csub\u003e2\u003c/sub\u003e in 50 mL H\u003csub\u003e2\u003c/sub\u003eO) at 37\u0026deg;C under gentle agitation for 60 minutes. Following centrifugation and resuspension cells were counted via trypan blue exclusion (1:1 dilution). Total cell numbers, live cell numbers and mean diameter were assessed using an automated cell counting system (Countess II FL, Invitrogen, USA).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eHistology analysis\u003c/h3\u003e\n\u003cp\u003e3D cell culture models were fixed in 4% paraformaldehyde (PFA), embedded in paraffin, and sectioned at 5 \u0026micro;m. Sections were stained with Hematoxylin and Eosin (H\u0026amp;E) and imaged using an all-in-one fluorescence microscope (BZ-X800, Keyence, Osaka, Japan).\u003c/p\u003e \u003cp\u003eQuantitative analysis was conducted using ImageJ Fiji (version 1.54f; National Institutes of Health, Bethesda, MD, USA). Regions of interest (ROIs) were manually defined, and tissue segmentation was performed via grayscale thresholding to generate binary masks. Total tissue area, nuclei count (via particle analysis), and apparent tissue thickness (vertical height of the bounding box) were calculated from calibrated images.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAll experimental procedures were performed using three to four independent samples per condition. Statistical evaluations were performed using GraphPad Prism 8 (GraphPad Software, San Diego, CA, USA). Data are expressed as mean\u0026plusmn;standard deviation (SD) and, where applicable, normalized to the corresponding 0 Gy control. To evaluate the effects of radiation dose, cell line, and culture system (2D vs. 3D), two-way analysis of variance (ANOVA) was employed. Multiple comparisons were conducted using Tukey\u0026rsquo;s post-hoc test to assess differences among multiple groups, while Sidak\u0026rsquo;s post-hoc test was used for comparisons between specific conditions (e.g., 2D vs. 3D). For histological and counting data where single factors were analysed, one-way ANOVA was applied. The consistency between different cell counting methodologies was evaluated using the Pearson correlation coefficient (r).\u003c/p\u003e \u003cp\u003eStatistical significance was defined as P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, with levels indicated as *p\u0026thinsp;\u0026lt;\u0026thinsp;0,05, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and ****p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eDeclaration\u003c/p\u003e \u003cp\u003eThis work was supported by JSPS KAKENHI Grant Number 23K11918.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eK. Igawa conceived the study, S.L. and I.Y. assisted by K.Igawa, K.Izumi and K.S. performed 2D and 3D cell culture experiments. Y.S. and N.K.provided thermal neturon source and performed the dose calculation. K.Igawa performed the neutron irradiation in 2D and 3D cell culture. S.L and I.Y. conducted the violability analysis and S.L. performed the histological analysis. S.L. and K.I wrote the manuscript with input from all authors. All authors discussed the results and commented on the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to thank all the staff at the Institute of Central Research Laboratory, Okayama University Medical School, for their assistance with the histological analysis and the Institute for Integrated Radiation and Nuclear Science, Kyoto University, for their technical assistance during the irradiation.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data supporting the findings of this study are included in this published article and its Supplementary Information files. The datasets are also publicly available from the Okayama University Scientific Achievement Repository, ousar.lib.okayama-u.ac.jp. Additional raw data are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eReport, I. C. R. U. 46, Photon, Electron, Proton and Neutron Interaction Data for Body Tissues \u0026ndash; ICRU. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.icru.org/report/photon-electron-proton-and-neutron-interaction-data-for-body-tissues-report-46/\u003c/span\u003e\u003cspan address=\"https://www.icru.org/report/photon-electron-proton-and-neutron-interaction-data-for-body-tissues-report-46/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarth, R. F., Coderre, J. A., Vicente, M. G. H. \u0026amp; Blue, T. E. Boron neutron capture therapy of cancer: current status and future prospects. \u003cem\u003eClin. Cancer Res.\u003c/em\u003e \u003cb\u003e11\u003c/b\u003e, 3987\u0026ndash;4002 (2005).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMentana, A. et al. Mapping neutron biological effectiveness for DNA damage induction as a function of incident energy and depth in a human sized phantom. \u003cem\u003eScientific Reports 2025 15:1\u003c/em\u003e 15, 2209- (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi, X. et al. Measurement of electrons from albedo neutron decay and neutron density in near-Earth space. \u003cem\u003eNature\u003c/em\u003e \u003cb\u003e552\u003c/b\u003e, 382\u0026ndash;385 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerrarini, M., EXPOSURE RISK FOR WORKERS \u0026amp; IN AN HADRONTHERAPY CENTRE AND COLLECTIVE AND INDIVIDUAL PROTECTION MEASURES. \u003cem\u003eG Ital. Med. Lav Ergon.\u003c/em\u003e \u003cb\u003e42\u003c/b\u003e, 257\u0026ndash;261 (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAzhgirey, I. L. \u0026amp; NEUTRON MONITORS FOR HIGH ENERGY ACCELERATORS.. https://doi.org/10.18429/JACoW-RUPAC2018-TUPSA38 (2018). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.18429/JACoW-RUPAC2018-TUPSA38\u003c/span\u003e\u003cspan address=\"10.18429/JACoW-RUPAC2018-TUPSA38\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIcrp \u0026amp; Annals of the ICRP Published on behalf of the International Commission on Radiological Protection.. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/ANIB_37_2-4\u003c/span\u003e\u003cspan address=\"10.1177/ANIB_37_2-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e doi:10.1177/ANIB_37_2-4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuzuki, M. Boron neutron capture therapy (BNCT): a unique role in radiotherapy with a view to entering the accelerator-based BNCT era. \u003cem\u003eInt. J. Clin. Oncol.\u003c/em\u003e \u003cb\u003e25\u003c/b\u003e, 43\u0026ndash;50 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoderre, J. A. \u0026amp; Morris, G. M. The Radiation Biology of Boron Neutron Capture Therapy. \u003cem\u003eRadiat. Res.\u003c/em\u003e \u003cb\u003e151\u003c/b\u003e, 1 (1999).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoodhead, D. T. Initial events in the cellular effects of ionizing radiations: clustered damage in DNA. \u003cem\u003eINT. J. RADIAT. BIOL.\u003c/em\u003e \u003cb\u003e65\u003c/b\u003e, 7\u0026ndash;17 (1994).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNikjoo, H., O\u0026rsquo;Neill, P., Terrissol, M. \u0026amp; Goodhead, D. T. Modelling of radiation-induced DNA damage: the early physical and chemical event. \u003cem\u003eInt. J. Radiat. Biol.\u003c/em\u003e \u003cb\u003e66\u003c/b\u003e, 453\u0026ndash;457 (1994).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoss, R. L. Critical review, with an optimistic outlook, on Boron Neutron Capture Therapy (BNCT). \u003cem\u003eAppl. Radiat. Isot.\u003c/em\u003e \u003cb\u003e88\u003c/b\u003e, 2\u0026ndash;11 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKapałczyńska, M. et al. 2D and 3D cell cultures \u0026ndash; a comparison of different types of cancer cell cultures. \u003cem\u003eArch. Med. Sci.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e, 910 (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantini, M. T., Rainaldi, G. \u0026amp; Indovina, P. L. Multicellular tumour spheroids in radiation biology. \u003cem\u003eInt. J. Radiat. Biol.\u003c/em\u003e \u003cb\u003e75\u003c/b\u003e, 787\u0026ndash;799 (1999).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHirschhaeuser, F. et al. Multicellular tumor spheroids: An underestimated tool is catching up again. \u003cem\u003eJ. Biotechnol.\u003c/em\u003e \u003cb\u003e148\u003c/b\u003e, 3\u0026ndash;15 (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAntonelli, F. 3D Cell Models in Radiobiology: Improving the Predictive Value of In Vitro Research. \u003cem\u003eInt. J. Mol. Sci.\u003c/em\u003e \u003cb\u003e24\u003c/b\u003e, 10620 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSharma, K., Dey, S., Karmakar, R. \u0026amp; Rengan, A. K. A comprehensive review of 3D cancer models for drug screening and translational research. \u003cem\u003eCancer Innov.\u003c/em\u003e \u003cb\u003e3\u003c/b\u003e, e102 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAizawa, Y. et al. Development and Characterization of a Three-Dimensional Organotypic In Vitro Oral Cancer Model with Four Co-Cultured Cell Types, Including Patient-Derived Cancer-Associated Fibroblasts. \u003cem\u003eBiomedicines\u003c/em\u003e 12, (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCharalampopoulou, A. et al. The rise of 3D spheroids in radiobiology for assessing tumour radioresistance. \u003cem\u003eActa Oncol.\u003c/em\u003e \u003cb\u003e65\u003c/b\u003e, 46\u0026ndash;58 (2026).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSakurai, Y. \u0026amp; Kobayashi, T. The medical-irradiation characteristics for neutron capture therapy at the Heavy Water Neutron Irradiation Facility of Kyoto University Research Reactor. \u003cem\u003eMed. Phys.\u003c/em\u003e \u003cb\u003e29\u003c/b\u003e, 2328\u0026ndash;2337 (2002).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYamamoto, I. et al. The Early Response After Radiation Therapy on Three-Dimensional Oral Cancer Model Using Patient-Derived Cancer-Associated Fibroblasts. \u003cem\u003eInt. J. Translational Med. 2025\u003c/em\u003e. \u003cb\u003e5\u003c/b\u003e (1), 12 (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFukuda, H. Response of normal tissues to boron neutron capture therapy (BNCT) with10 b-borocaptate sodium (BSH) and 10 b-paraboronophenylalanine (BPA). \u003cem\u003eCells\u003c/em\u003e \u003cb\u003e10\u003c/b\u003e (11), 2883 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark, H. J., Griffin, R. J., Hui, S., Levitt, S. H. \u0026amp; Song, C. W. Radiation-induced vascular damage in tumors: implications of vascular damage in ablative hypofractionated radiotherapy (SBRT and SRS). \u003cem\u003eRadiat. Res.\u003c/em\u003e \u003cb\u003e177\u003c/b\u003e, 311\u0026ndash;327 (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHirose, K., Sato, M., Ichise, K. \u0026amp; Aoki, M. Dose Rate Effect on Cell Survival in BNCT. \u003cem\u003eCurr. Issues Mol. Biol.\u003c/em\u003e \u003cb\u003e45\u003c/b\u003e, 6986\u0026ndash;6994 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaitanen, J. et al. Comparison of radiation response between 2D and 3D cell culture models of different human cancer cell lines. \u003cem\u003eCells\u003c/em\u003e \u003cb\u003e12\u003c/b\u003e, 360 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKato, I. et al. Effectiveness of boron neutron capture therapy for recurrent head and neck malignancies. \u003cem\u003eAppl. Radiat. Isot.\u003c/em\u003e \u003cb\u003e67\u003c/b\u003e, 7\u0026ndash;8 (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIgawa, K., Izumi, K. \u0026amp; Sakurai, Y. Development of the Follow-Up Human 3D Oral Cancer Model in Cancer Treatment. \u003cem\u003eBioTech. 2023\u003c/em\u003e. \u003cb\u003e12\u003c/b\u003e (2), 35 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu, L. S. et al. Tissue architecture influences the biological effectiveness of boron neutron capture therapy in in vitro/in silico three-dimensional self-assembly cell models of pancreatic cancers. \u003cem\u003eCancers (Basel)\u003c/em\u003e. \u003cb\u003e13\u003c/b\u003e, 4058 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarcellos-Hoff, M. H., Park, C. \u0026amp; Wright, E. G. Radiation and the microenvironment - tumorigenesis and therapy. \u003cem\u003eNat. Rev. Cancer\u003c/em\u003e. \u003cb\u003e5\u003c/b\u003e, 867\u0026ndash;875 (2005).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrisnawan, V. E., Stanley, J. A., Schwarz, J. K. \u0026amp; Denardo, D. G. Tumor Microenvironment as a Regulator of Radiation Therapy: New Insights into Stromal-Mediated Radioresistance. \u003cem\u003eCancers (Basel)\u003c/em\u003e. \u003cb\u003e12\u003c/b\u003e, 1\u0026ndash;25 (2020).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-9354079/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9354079/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn radiation therapy, accurately estimating the relative biological effectiveness (RBE) is essential for the safe and effective clinical application of neutron radiation therapy. Current RBE evaluations primarily rely on two-dimensional (2D) colony formation assays. However, these models cannot fully capture tissue-level complexity and are not applicable to normal cells lacking colony-forming ability. This limits their clinical applicability. This study demonstrated that the dimensionality of the culture is a critical determinant of radiation sensitivity. While the biological effectiveness of neutron irradiation is systematically overestimated in conventional 2D monolayer systems, three-dimensional (3D) tissue-mimicking models more accurately reproduce the resistance of normal tissues observed in clinical settings. Specifically, we identified a dose-dependent thinning of the extracellular matrix at doses of 25 Gy or higher, suggesting that neutron-induced damage extends beyond cell death to include structural and microenvironmental damage. These findings offer direct insights into the estimation of clinical doses and the protection of normal tissues. While further refinement of model parameters, including cell density and microenvironmental composition, is necessary, the proposed 3D platform provides a clinically meaningful framework for evaluating radiation-induced toxicity in non-colony-forming normal tissues. By facilitating a more precise evaluation of radiation-induced tissue effects, this methodology has the potential to enhance the estimation of RBE and risk stratification, thus contributing to the development of more secure treatment protocols and the broader implementation of neutron therapy.\u003c/p\u003e","manuscriptTitle":"Bridging the translational gap in radiotherapy: a human three-dimensional cell culture for evaluating neutron biological effects","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-30 15:16:07","doi":"10.21203/rs.3.rs-9354079/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-19T08:33:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-19T06:34:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"334289973027791047577416961213653448989","date":"2026-04-22T01:53:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"199596297976302988273160233982438581693","date":"2026-04-21T23:53:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"136382068828733604341350350735314615026","date":"2026-04-21T23:18:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-21T23:04:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-18T15:21:59+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-17T14:01:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-15T02:58:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-04-15T02:53:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0718c256-922e-4147-936c-603b4ad0b8ca","owner":[],"postedDate":"April 30th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-19T08:33:32+00:00","index":31,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-19T06:34:20+00:00","index":30,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":66773027,"name":"Biological sciences/Biophysics"},{"id":66773028,"name":"Biological sciences/Cancer"},{"id":66773029,"name":"Health sciences/Medical research"},{"id":66773030,"name":"Health sciences/Oncology"},{"id":66773031,"name":"Physical sciences/Physics"}],"tags":[],"updatedAt":"2026-04-30T15:16:07+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-30 15:16:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9354079","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9354079","identity":"rs-9354079","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}