Quantitative Study on Hepatic Genotoxicity of Neodymium and Its Molecular Mechanisms Based on Benchmark Dose Method

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To clarify the genotoxic effects of intragastric neodymium nitrate (Nd(NO 3 ) 3 ) administration over 28 consecutive days, we assessed the percentage of tail DNA in mouse hepatocytes using the alkaline comet assay, genetic toxicological biomarkers, and the expression levels of genes and proteins related to the p53 pathway in the mouse liver. Our results indicated significant accumulation of Nd(NO 3 ) 3 in the livers and kidneys of mice, resulting in micronuclei formation and DNA double-strand breaks, as indicated by comet and γ-H2AX assays, as well as DNA damage in hepatocytes. Nd(NO 3 ) 3 significantly increased the percentage of tail DNA in hepatocytes as measured by the alkaline comet assay and upregulated the expression of p53 pathway-related molecules, including ATM, Wip1, ATR, Chk2, MDM2, p53, p21, and NF-kB, at both the transcriptional and translational levels. This treatment effectively triggered the production of reactive oxygen species (ROS), 8-hydroxy-2'-deoxyguanosine (8-OHdG), and γ-H2AX in liver tissue. These findings suggest that Nd(NO 3 ) 3 induces hepatic genotoxicity and injury in mice, and modulates the expression of genes associated with DNA damage response, carcinogenesis, and inflammatory processes. Health sciences/Medical research Health sciences/Risk factors Figures Figure 1 Figure 2 Figure 3 Figure 4 1.1 Introduction Rare earth elements (REEs) encompass the 17 elements of the lanthanide series, including lanthanum, cerium, praseodymium, neodymium (Nd), and others, with scandium and yttrium often included due to their similar chemical properties. Their unique physical and chemical attributes, such as high reactivity and low ignition points, have led to broad applications across various sectors, including industry, agriculture, medicine, and high-tech fields [ 36 ] (US EPA, 2012). Notably, REEs are integral to the production of glass, ceramics, magnets, electronics, superconductors, and lasers, with neodymium's role in manufacturing magnets for speakers, computer hard drives, wind turbines, and hybrid vehicles being particularly significant [ 23 ] (Kyung et al., 2013; Hirano et al., 1996). Additionally, fertilizers enriched with lanthanum, cerium, and neodymium have been reported to boost crop yields in China [ 18 ] (Hu et al., 2004; Ni, 2002). However, the surge in REE mining and industrial use has resulted in their widespread release into the environment, raising concerns about potential accumulation and pollution in soil, vegetation, water, and air [ 19 ] (Huang, 2019). Neodymium, detected as the third most abundant REE in Chinese soil with a background value of 25.1 mg/kg, follows cerium at 64.7 mg/kg and lanthanum at 37.4 mg/kg, and is considered potentially highly toxic [ 42 ] (Wang et al., 2022). This has heightened the interest in neodymium's potential benefits and the associated environmental and health risks [ 27 , 12 ] (Ma et al., 2022; Freitas, 2020). Human exposure to REEs occurs through the digestive tract, respiratory system, and skin, with detectable levels in blood, urine, and hair [ 47 ] (Zhao et al., 2011). Evidence from animal studies and occupational exposure suggests that REEs can bioaccumulate and cause damage to vital organs such as the lungs, liver, and brain [ 26 ] (Liu et al., 2008). Specifically, neodymium has been implicated in oxidative damage within hepatocytes, affecting both the nuclei and mitochondria [ 34 ] (Peili H et al., 2011). The liver, lungs, and blood are recognized as primary targets for REE-induced toxicity [ 40 ] (Sturla et al., 2021), with light REEs, including neodymium, tending to accumulate in the liver and spleen [ 37 ] (Ruan et al., 2011). Studies have also linked Nd(NO 3 ) 3 exposure to liver tissue damage, oxidative stress, and inflammation in rats [ 25 , 13 , 11 ] (Liao et al., 2009; Gao et al., 2020; Fei et al., 2011). Despite the evidence of neodymium's genotoxic potential, the underlying mechanisms and long-term health impacts remain unclear, underscoring the need for further research. This study posits that neodymium nitrate's genotoxicity may be mediated through the p53 signaling pathway, a canonical route in DNA damage response. Using the OECD-recommended in vivo comet assay, we assessed neodymium nitrate's genotoxicity and investigated the correlation between hepatic neodymium content and subacute genotoxic effects. We further explored the impact of neodymium nitrate on oxidative stress markers (ROS, 8-OHdG, γ-H2AX) and p53 pathway components to delineate the mechanism of its genotoxicity. The determination of a Point of Departure (PoD) for human health risk assessment is a critical aspect of quantitative genetic evaluation. The Benchmark Dose (BMD) approach, endorsed by the International Workshop on Genotoxicity Testing (IWGT), is a prominent method for deriving PoD thresholds [ 28 , 35 ] (MacGregor JT et al., 2015; Pottenger IH et al., 2014). The BMD is calculated using specific software and models to identify the dose at which a predetermined response level change, the benchmark response (BMR), occurs [ 15 , 8 , 21 ] (Hardy A et al., 2016; EFSA, 2018; IZADI H et al., 2012). The p53 gene, a pivotal tumor suppressor and the "guardian of the genome," is central to cellular responses to DNA damage and other stressors [ 3 , 24 ] (Chen et al., 2019; Lahav et al., 2004). This study examines the role of p53 pathway components in neodymium nitrate-induced DNA damage and p53 response modulation. Adhering to OECD guidelines [ 32 , 33 ] (OECD 489, 2016), we evaluated hepatocyte DNA damage and oxidative stress markers to assess neodymium nitrate's genotoxic potential. Our research aims to innovate toxicity assessment and risk prediction methodologies, enhancing chemical risk analysis, disease surveillance, and pharmaceutical research. 1.2 Materials and Methods 1.2.1 Chemicals and Reagents Neodymium nitrate hexahydrate [Nd(NO 3 ) 3 ·6H 2 O] was obtained from Sigma-Aldrich with a CAS number of 16454-60-7 and a purity of 99.9%. Ethyl methanesulfonate, used as a positive control, was also sourced from a reliable chemical supplier. 1.2.2 Animal Model and Treatment Regimen Six-week-old ICR mice, weighing 29 ± 5 grams, were procured from Zhejiang Weitong Lihua Experimental Animal Technology Co., Ltd (China). Thirty male mice were housed under controlled conditions with a temperature of 22 ± 2℃, relative humidity of 60 ± 5%, and a 12-hour light/dark cycle. They were provided with food and water ad libitum and allowed a 5-day acclimation period prior to the experiment. The study was approved by the International Ethics Committee on Animal Welfare, and all procedures were conducted in accordance with their guidelines. The mice were randomly assigned into seven groups: a negative control, a positive control, and five experimental groups receiving Nd(NO 3 ) 3 at dosages of 7, 27, and 55mg/kg body weight (n = 6 per group). The dosages for the 28-day subacute toxicity study were determined based on an acute genotoxicity test using a dose of 39mg/kg for male mice. Nd(NO 3 ) 3 was administered daily by gavage for 28 days. The negative control group received an equivalent volume of purified water, while the positive control group received ethyl methanesulfonate (200mg/kg) in purified water. Daily observations of symptoms and mortality were recorded throughout the study. At the conclusion of the treatment period, blood was collected via the retro-orbital plexus method for neodymium content analysis. Mice were euthanized by cervical dislocation, and liver samples were collected for comet assay, qRT-PCR, ELISA, and histopathological examination. 1.2.3 In Vivo Comet Assay The in vivo comet assay was performed in accordance with OECD Test Guideline 489 (OECD, 2016). Three hours post the final administration, mice were euthanized, and single liver cells were isolated from the left lateral lobe. A commercial comet assay kit (Cat. BR-0904, BIOLAB Company) was utilized for the procedure. Liver cells were embedded in low-melting agarose and subjected to lysis at 4℃ for 1 hour. Following lysis, slides were neutralized, incubated in an alkaline solution to allow DNA unwinding, and then electrophoresed. Slides were subsequently stained with Gelred, rinsed, and analyzed using a Leica DM3000 fluorescence microscope equipped with a fiber optic lamp and a ×200 magnification lens. The Comet Intelligence Analysis software was employed for scoring DNA damage by quantifying the % tail DNA in 150 cells per sample. 1.2.4 Determination of Neodymium Content in Livers by ICP-MS Liver tissue samples were digested in microwave digestion tubes with 5 mL of trace metal-grade nitric acid (CNW Technologies) using a microwave digestion system. The digestion program consisted of three steps: ① 5 min at 120℃ with a 5 min hold; ② 5 min at 150℃ with a 10 min hold; ③ 5 min at 190℃ with a 20 min hold. After cooling, samples were subjected to acid removal at 120℃ for approximately 30 min, then diluted to 25.0 mL with ultrapure water (18.2 MΩ·cm, Milli-Q), and mixed thoroughly. Analysis was performed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS; Agilent 8900 ICP-MS/MS, Agilent Technologies, USA) with the following parameters: RF power 1500W, concentric nebulizer, plasma gas flow 15 L/min, nickel sampling cone/skimmer cone, carrier gas flow 0.80 L/min, sampling depth 10 mm, auxiliary gas flow 0.40 L/min, peak hopping acquisition mode, helium flow 4.3 mL/min, automatic detection mode, atomization chamber temperature 2℃, three measurement points per peak, sample lift rate 0.3 r/s, and three repetitions. Indium (50 ng/mL) served as the internal standard. The neodymium detection limit was 0.0018 ng/mL, with data expressed as nanograms per gram of fresh tissue. 1.2.5 γ-H2AX Liver Content by ELISA Approximately 50 mg of liver tissue was snap-frozen in liquid nitrogen for γ-H2AX content determination using an ELISA kit (Mouse γH2AX ELISA KIT, Shanghai Enzyme Union Biotechnology Co., LTD). Liver samples were homogenized in Hank’s Balanced Salt Mixture (D-Hanks, without Ca 2+ and Mg 2+ , without phenol red, pH 7.4) and centrifuged at 2000–3000 rpm for 20 min. The supernatant was collected for immediate testing or stored at -20℃ to avoid repeated freezing and thawing. Protein content was measured by the Lowry method (Lowry et al., 1951), with triplicate analyses for each sample. 1.2.6 Liver ROS Content by ELISA ROS content in liver tissue was determined using a similar ELISA protocol (Mouse ROS ELISA Kit, Shanghai Enzyme-Linked Biotechnology Co., Ltd.). Samples were processed and analyzed as described for γ-H2AX, with the same conditions for homogenization, centrifugation, and storage. 1.2.7 Liver 8-OHdG Content by ELISA The content of 8-OHdG in liver tissue was measured by ELISA (Mouse 8-OHdG ELISA Kit, Shanghai Enzyme-Linked Biotechnology Co., Ltd.) following the same homogenization, centrifugation, and storage procedures as the previous assays. The protein content was determined by the Lowry method, and triplicate analyses were conducted for each sample. 1.2.8 cDNA Sample Preparation from Mouse Liver Total RNA was extracted using the Total RNA Extraction Kit (TIANGEN BIOTECH, DP451, Item number: 4992562, Lot number: Y1209). The purity of RNA was confirmed with an A260/A280 ratio of 2.1, indicating sufficient freedom from protein contamination. Reverse transcription was performed using the FastKing gDNA Dispelling RT SuperMix (TIANGEN BIOTECH, KR118-02, Lot number: X1010). The resulting cDNA was resuspended in Tris-HCl buffer (pH 7.2) and stored at 4°C. mRNA expression levels were determined by qRT-PCR with the SuperReal PreMix Plus (SYBR Green, TIANGEN BIOTECH, FP205-02, Lot number: X1018), using β-actin as an internal control. Primer sequences were identified through a literature search [ 37 ] (Qin Luo et al., 2018) and synthesized by Sangon Biotech. Primer details are presented in Table 1 . Table 1 Primer Pairs Used for Gene Expression Analysis by qRT-PCR Gene Name Primer Sequence(5' to 3') Base Pair Count Provide Total Quantity(OD) Purification Method ATM gene CCAAGATGGCAGTGAACCAGAC-F; 24 2OD HPLC ATGCTGGACAGCTATGGTGGAG-R; 23 2OD HPLC Wip1 gene TCACAGTGGACCTGTCAGAAGG-F; 24 2OD HPLC AGAGTGTGGACACTGGTGTCTG-R; 23 2OD HPLC ATR gene GAAAGAGGCTCCTACCAACGAG-F; 23 2OD HPLC CAACTGTCACCTGGAGACTTGC-R; 23 2OD HPLC Chek2 gene GAGGTTCTTGTCTCCAACGGGA-F; 23 2OD HPLC ATCCTTCAGGGACACTTGGGTC-R; 23 2OD HPLC MDM2 gene CCGAGTTTCTCTGTGAAGGAGC-F; 24 2OD HPLC GTCTGCTCTCACTCAGCGATGT-R; 23 2OD HPLC β-actin gene CATTGCTGACAGGATGCAGAAGG-F; 24 2OD HPLC TGCTGGAAGGTGGACAGTGAGG-R; 23 2OD HPLC p53 gene AGAGACCGCCGTACAGAAGA-F; 22 2OD HPLC GCATGGGCATCCTTTAACTC-R; 21 2OD HPLC p21 gene TCGCTGTCTTGCACTCTGGTGT-F; 23 2OD HPLC CCAATCTGCGCTTGGAGTGATAG-R; 24 2OD HPLC NF-kB gene TCCTGTTCGAGTCTCCATGCAG-F; 23 2OD HPLC GGTCTCATAGGTCCTTTTGCGC-R; 23 2OD HPLC 1.2.9 Expression Analysis of p53 Pathway-Related Genes The mRNA expression levels of ATM, Wip1, ATR, Chk2, MDM2, p53, p21, caspase3, and NF-kB were quantified by qRT-PCR. Liver samples from mice of the same growth phase, with or without Nd(NO 3 ) 3 treatment, were homogenized, and total RNA was isolated using the aforementioned RNA extraction kit. The FastKing gDNA Dispelling RT SuperMix was used for cDNA synthesis under the following conditions: 42℃ for 15 min, followed by 95℃ for 3 min. Primers for qRT-PCR were designed using Primer Express Software and synthesized by Sangon Biotech (China). The qRT-PCR reaction mixture was prepared with SuperReal Premix Plus and consisted of a three-step cycling program: 95℃for 15 min, followed by 40 cycles of 95℃ for 10 s, 58℃ for 20 s, and 72℃ for 30 s. Gene expression analysis was conducted using standard curve and quantitation methods. 1.2.10 Statistical Analysis Data were analyzed using GraphPad Prism 8 and presented as means ± standard error (SE). One-way ANOVA was used to assess differences among multiple groups, followed by Tukey's HSD for pairwise comparisons with the control group, with significance set at p < 0.05. For the Benchmark Dose (BMD) analysis, we utilized the e(BMD) model with Benchmark Dose Software (BMDS, version 3.2) following USEPA guidance. The best-fit model was selected based on the lowest Akaike Information Criterion (AIC) to calculate parameters such as BMD, BMDL, and BMDU, representing the BMD and its 95% confidence intervals. The BMD 50 was used for all analyses, corresponding to a 50% increase in genotoxicity test frequency over background. Data were batched by exposure route and analyzed using combined covariate BMD modeling to ensure consistency and computational feasibility. The Index and Hill model family, recommended by EFSA for continuous data analysis, were applied. Covariate analysis assumed constant model parameters for maximum response and steepness of the dose-response curve. Unique identifiers were assigned to datasets with different parameters, used as covariates for background response, efficacy, and within-group variance. For compounds with multiple datasets, the lowest BMDL value was used for MOE calculations. 1.3 Result 1.3.1 Effect of 28-Day Neodymium Nitrate Administration on Body Weight of ICR Mice The weekly body weight changes of ICR mice following 28 days of continuous Nd(NO 3 ) 3 administration are depicted in Fig. 1 -A. No significant differences in body weight were observed between the treatment groups and the solvent control group (P > 0.05). There were no noticeable changes in the general health of the treatment groups compared to the control group. Post-administration, some individual mice exhibited signs of lethargy, reduced mobility, and dulled fur; however, these symptoms did not present a consistent pattern. 1.3.2 Determination of Neodymium Content in the Liver of ICR Mice After 28 Days of Administration 1.3.2.1 Limit of Detection (LOD) and Limit of Quantitation (LOQ) The method's detection limit was established at 0.0018 µg/L based on the mean response plus three times the standard deviation of 11 blank samples' responses. Recovery rates were between 97.2% and 111.0%, and relative standard deviations ranged from 1.63–7.93%. The inductively coupled plasma mass spectrometer was calibrated using a mass spectrometry tuning solution to ensure optimal performance. A 10.0 µg/mL neodymium (Nd) standard stock solution was serially diluted with 1% nitric acid to create a calibration range of 0.05, 0.1, 0.5, and 1.0 µg/L. Indium (In) served as the internal standard. A calibration curve was generated with the y-axis representing the ratio of the signal values of neodymium to indium and the x-axis representing the neodymium content. The linear correlation coefficient was 0.9993, indicating that the method's performance meets the detection criteria. 1.3.2.2 Determination of Neodymium Content in the Liver of ICR Mice After continuous administration of Nd(NO 3 ) 3 for 28 days, the changes in neodymium content in the tissues and organs of ICR mice are shown in Figs. 1 -B and C. It can be observed that: In liver, it began to significantly exceed the solvent control group from a dosage of 14 mg/kg body weight (P values were 0.0008, 0.0003, < 0.0001, and < 0.0001). In hepatocytes, the neodymium content in male mice, it began to significantly exceed the solvent control group from a dosage of 39 mg/kg body weight (P values were 0.0119 and < 0.0001). 1.3.3 DNA Damage in Liver Tissue Cells Induced by 28-Day Neodymium Nitrate Administration In the neodymium nitrate treatment groups, DNA breaks were observed, characterized by the presence of orange-red fluorescent nuclei and comet-shaped tails in the cells. At a treatment concentration of 55 mg/kg body weight (BW), the percentage of tail DNA content in liver cells of ICR mice was significantly increased compared to the control group, with a statistically significant difference (P = 0.0003). Similarly, in the positive control group treated with Ethyl Methanesulfonate (EMS) at a dose of 200 mg/kg BW, the percentage of tail DNA content in liver cells of male ICR mice was significantly higher than that of the control group (P = 0.0003), as shown in Fig. 1 -D. A dose-response relationship was observed as the treatment dosage of neodymium nitrate increased, with a continuous rise in the percentage of tail DNA content in mouse liver cells. The Benchmark Dose Lower Limit (BMDL) for the percentage of tail DNA content in liver cells of male ICR mice was 17.32 mg/kg, and the Benchmark Dose (BMD) value was 31.63 mg/kg, as depicted in Fig. 1 -E. 1.3.4 Correlation Analysis of Neodymium Content in Liver and Liver Cells After 28 Days of Neodymium Nitrate Administration The neodymium content in the blood and the dosage of administration showed significant correlations with all assessed indicators (P < 0.05). Notably, the percentage of DNA content in the tail of liver cells correlated significantly with both the neodymium content in the liver and the liver cells (P < 0.05). As shown in Fig. 1 -F. 1.3.5 Effects of 28-Day Neodymium Nitrate Administration on Liver Tissue Biomarkers γ-H2AX Content: At a dosing concentration of 55 mg/kg body weight (BW), the liver tissue γ-H2AX content in male ICR mice was significantly elevated compared to the control group (P = 0.0345). In the positive control group administered Ethyl Methanesulfonate (EMS) at 200 mg/kg BW, the γ-H2AX content was also significantly higher than in the control group (P < 0.0001). As shown in Fig. 2 -A. An increase in γ-H2AX content with dose escalation was observed, indicating a clear dose-response relationship. The Benchmark Dose Lower Limit (BMDL) for γ-H2AX content in liver tissue of male ICR mice was 20.74 mg/kg, with a Benchmark Dose (BMD) of 34.40 mg/kg. As depicted in Fig. 2 -D. ROS Content: At dosing concentrations of 14, 39, and 55 mg/kg BW, the liver tissue ROS content in male ICR mice was significantly higher than in the control group (P < 0.0001 for all doses). In the EMS positive control group at 200 mg/kg BW, ROS content was also significantly increased compared to the control group (P < 0.0001). As shown in Fig. 2 -B. A dose-response relationship was evident as the dosing concentration of neodymium nitrate increased. The BMDL for ROS content in liver tissue was 18.32 mg/kg, and the BMD was 24.21 mg/kg. As shown in Fig. 2 -E. 8-OHdG Content: At a dosing concentration of 55 mg/kg BW, the liver tissue 8-OHdG content in male ICR mice was significantly higher than in the control group (P < 0.0001). Similarly, in the EMS positive control group at 200 mg/kg BW, the 8-OHdG content was significantly elevated compared to the control group (P < 0.0001). As shown in Fig. 2 -C. An increase in 8-OHdG content with dose escalation was observed, consistent with a dose-response relationship. The BMDL for 8-OHdG content in liver tissue was 20.51 mg/kg, with a BMD of 29.90 mg/kg. As shown in Fig. 2 -F. 1.3.6 Effects of 28-Day Neodymium Nitrate Administration on the Relative RNA Expression of p53 Pathway Genes in Liver Tissue of Male ICR Mice RNA extraction was performed using the Tiangen Animal Tissue and Cell Total RNA Extraction Kit (DP451) following the manufacturer's protocol. Reverse transcription was conducted using the Tiangen One-Step gDNA Removal cDNA Synthesis Kit (KR118). Quantitative real-time PCR (qRT-PCR) was used to assess mRNA expression levels with the Tiangen SuperReal PreMix Plus (SYBR Green) as the fluorescent quantitative premixed reagent, using β-actin as the internal control. Primers were selected based on a literature search (Haiquan Zhao et al., 2012). In male ICR mice, the relative RNA expression of the following genes showed significant increases compared to the control group at the indicated neodymium nitrate dosing concentrations: - ATM: At 27 and 55 mg/kg body weight (BW), with P-values of 0.0239 and 0.0004, respectively. - Wip1: At 27 and 55 mg/kg BW, with P-values of 0.0097 and 0.0003, respectively. - ATR: At 27 and 55 mg/kg BW, with P-values of 0.0030 and 0.0002, respectively. - MDM2: At 27 and 55 mg/kg BW, with P-values of 0.0004 and < 0.0001, respectively. - p53: At 7 and 27 mg/kg BW, with P-values of 0.0019 and 0.0379, respectively. - p21: At 7, 27, and 55 mg/kg BW, with P-values of 0.0464, 0.0070, and 0.0005, respectively. - NF-kB: At 7, 27, and 55 mg/kg BW, with P-values of 0.0310, 0.0020, and < 0.0001, respectively. - Chk2: At 27 and 55 mg/kg BW, with P-values of 0.0065 and < 0.0001, respectively. All observed differences were statistically significant, indicating a dose-dependent effect of neodymium nitrate on the expression of these genes. As shown in Fig. 3 -A. BMD calculations for the relative RNA expression of p53 pathway genes in the liver tissue of male ICR mice after 28 days of neodymium nitrate administration were performed, and the BMD values for each gene in the p53 pathway are depicted in Figs. 3 -B, C, D, E, F, G, H, and I. A summary of the BMD values for the genes in the p53 pathway is presented in Table 2 . Table 2 BMD Calculation for qPCR Quantitative Analysis p53 Molecular Pathway Gene BMD(mg/kg) BMDL(mg/kg) ATM gene 8.17 5.86 Wip1 gene 5.94 3.37 ATR gene 4.40 2.61 MDM2 gene 3.63 2.39 p53 gene 51.72 29.07 p21 gene 2.84 1.04 NF-kB gene 10.22 7.76 ChK2 gene 11.32 8.72 1.4 Discussion Traditional genotoxicity testing paradigms, established in the 1970s and 1980s in North America, Japan, and Europe, have been pivotal in dichotomously classifying chemicals as genotoxic or non-genotoxic. This binary categorization has underpinned risk management strategies for decades. However, the advent of high-throughput testing technologies has unveiled complex, non-linear dose-response relationships, particularly at low doses. Aneugens like colchicine and mutagenic substances such as methyl sulfonate demonstrate curved dose-response patterns, suggesting that biological responses to these agents may entail both dose-dependent and threshold mechanisms. These insights necessitate a reevaluation of existing models and a more nuanced understanding of dose-response dynamics, especially at lower exposure levels, to accurately assess chemical safety and potential human health risks. Quantitative genotoxicity risk assessment has advanced beyond qualitative methods, offering a more refined tool for evaluating health risks. The traditional ALARA principle has been augmented by quantitative approaches that calculate the margin of exposure (MOE), the ratio of acceptable exposure levels to actual or anticipated human exposure. This metric facilitates a more precise estimation of health risks associated with genotoxicants. Quantified measures like MOEs and reference doses enhance the ability of risk managers to prioritize and control genotoxic substances effectively and communicate the magnitude of risks to the public and policymakers. In this study, 28 days of continuous neodymium nitrate (Nd(NO 3 ) 3 ) administration to ICR mice revealed no significant body weight changes compared to the control group, suggesting minimal toxicity within the tested dosage range (7–55 mg/kg for males). ICP-MS analysis indicated liver accumulation of neodymium, highlighting the liver as a primary target organ. Our findings indicate potential genotoxic effects of Nd(NO 3 ) 3 in mice, with implications for human exposure. Hepatocyte alkaline comet assays were conducted in accordance with OECD guidelines, providing precise DNA damage measurements. A quantitative genotoxicity assessment using the Benchmark Dose (BMD) approach allowed us to calculate the MOE for human health risks, offering a comprehensive evaluation of Nd(NO 3 ) 3 genotoxicity. Correlation analysis between liver neodymium concentration and genotoxicity outcomes post-Nd(NO 3 ) 3 administration revealed significant associations, suggesting a dose-dependent genotoxic effect. The biomarker analysis further confirmed Nd(NO 3 ) 3 -induced genotoxicity and its DNA damaging effects on hepatocytes. The p53 signaling pathway, a critical biomarker in genotoxicity research, was examined for its role in the molecular response to Nd(NO 3 ) 3 . Our analysis of BMD (Benchmark Dose) and BMDL (Benchmark Dose Lower Limit) values for genes in the p53 pathway, including ATM, Wip1, ATR, MDM2, p53, p21, NF-κB, and Chk2, along with comet assay and genotoxicity biomarker data, identified p21, MDM2, and Wip1 as potential early indicators of DNA damage. These findings provide a theoretical foundation for understanding the genotoxicity mechanism of Nd(NO 3 ) 3 , as illustrated in Fig. 4 . As a cyclin-dependent kinase inhibitor, p21 is intricately linked to tumor suppression, regulating cell cycle, DNA replication, and repair processes. qRT-PCR analysis of the p53 pathway and downstream genes revealed significant upregulation of ATM, ATR, Wip1, MDM2, p21, and Chk2, suggesting a close relationship between Nd(NO 3 ) 3 -induced liver genotoxicity and the p53 pathway, with implications for cell cycle arrest. Declarations All experiments involving live vertebrates were conducted in accordance with the guidelines and regulations set forth by the Shanghai Center for Disease Control and Prevention & Shanghai Institute of Preventive Medicine of the Institutional Animal Care and Use Committee (IACUC). The study was approved by the Shanghai Center for Disease Control and Prevention & Shanghai Institute of Preventive Medicine, with the approval number KY20230002. All efforts were made to minimize animal suffering and to reduce the number of animals used for the experiments. The ARRIVE guidelines ( https://arriveguidelines.org ) were followed to ensure the comprehensive and transparent reporting of the methods and results of the animal experiments. Conflict of Interests We declare no conflict of interests. Author Contribution The primary manuscript text was written by Ning Wang, Xiu-li Chang, Jing Leng, Xin-yu Hong, and Xu-dong Jia. Figures 1 to 3 were completed by Xue-qing Cheng, Yu Ding, Jing Xu, Zhengli Yang, Hui-min Zhang, and Jing-qiu Sun. All authors have reviewed the manuscript. Acknowledgments This work was supported by the Food Toxicology Program, of the National Center for Food Safety Risk Assessment. Data Availability we have uploaded the data to the OMIX repository, with the accession number: OMIX007180, and have added a data availability statement at the end of the manuscript in section 1.7. 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Endocrinology and Metabolism Clinics of North America, 2014,43(1):1-23. Soeteman-Hernandez, L.G., Johnson, G.E. & Slob, W. (2016) Estimating the carcinogenic potency of chemicals from the in vivo micronucleus test. Mutagenesis, 31, 347-358. Sturla Lompré, J., et al., Bioaccumulation and ecotoxicological responses of clams exposed to terbium and carbon nanotubes: Comparison between native (Ruditapes decussatus) and invasive (Ruditapes philippinarum) species. Sci Total Environ, 2021. 784: 146914. Wang YJ., et al., Progress in p53 in DNA damage response. Journal of Pharmacy, 2011,46 (12): 1413-1419. Wang ZW, et al., soil distribution characteristics and environmental significance of rare earth elements in typical facility vegetable fields in northern China. Environmental Science, 2022,43 (4): 2071-2080. Wassom JS, et al., Reflections on the origins and evolution of genetic toxicology and the Environmental Mutagen Society. Environ Mol Mutagen. 2010, 51(8/9):746-760. Wills, J.W., Johnson, G.E., Battaion, H.L., Slob, W. & White, P.A. (2017), Comparing BMD-derived genotoxic potency estimations across variants of the transgenic rodent gene mutation assay. Environmental and Molecular Mutagenesis, 58, 632–643. Zeller A., et al., A proposal for a novel rationale for critical effect size in dose-response analysis based on a multi-endpoint in vivo study with methyl methanesulfonate. Mutagenesis, 2016,31(3):239-253 Zhang XY., et al., Progress in p53-independent signaling in DNA damage-induced apoptosis. Journal of Zhejiang University (Medical edition), 2013,42 (2): 217-223. Zhao, H., et al., Oxidative injury in the brain of mice caused by lanthanid. Biol Trace Elem Res, 2011. 142(2): 174-89. Additional Declarations No competing interests reported. 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The effect of 28-day neodymium nitrate administration on the body weight of ICR mice, B. The effect of 28-day neodymium nitrate administration on the neodymium content in the livers of ICR mice, C. The effect of 28-day neodymium nitrate administration on the neodymium content in the liver cells of ICR mice, D. Comet assay photos of hepatocytes from ICR mice in various dosage groups and the percentage of DNA in the tail of hepatocyte comets, E. Benchmark Dose (BMD) for the percentage of DNA in the tail of hepatocyte comets of ICR mice, F. Correlation analysis of neodymium content in the livers and liver cells of ICR mice after 28 days of neodymium nitrate administration, including dosing levels and the percentage of tail DNA content in liver cells).\u003c/p\u003e\n\u003cp\u003e(*: Compared with the negative control group, P \u0026lt; 0.05; **: Compared with the negative control group, P \u0026lt; 0.01; ***: Compared with the negative control group, P \u0026lt; 0.001; ****: Compared with the negative control group, P \u0026lt; 0.0001)\u003c/p\u003e","description":"","filename":"Figure12.png","url":"https://assets-eu.researchsquare.com/files/rs-4911449/v1/839f3061947db335f57ccb62.png"},{"id":65252714,"identity":"be2ad5f4-2c5b-4ccd-a0a7-7447ec14dd5d","added_by":"auto","created_at":"2024-09-25 09:11:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":239037,"visible":true,"origin":"","legend":"\u003cp\u003eDetermination of γ-H2AX, ROS, and 8-OHdG content in liver tissue of male ICR mice after 28 days of neodymium nitrate administration (A. γ-H2AX content in liver tissue of ICR mice, B. ROS content in liver tissue of ICR mice, C. 8-OHdG content in liver tissue of ICR mice, D. Benchmark dose (BMD) values for γ-H2AX content in liver tissue of ICR mice, E. Benchmark dose (BMD) values for ROS content in liver tissue of ICR mice, F. Benchmark dose (BMD) values for 8-OHdG content in liver tissue of ICR mice).\u003c/p\u003e\n\u003cp\u003e(*: Compared with the negative control group, P \u0026lt; 0.05; **: Compared with the negative control group, P \u0026lt; 0.01; ***: Compared with the negative control group, P \u0026lt; 0.001; ****: Compared with the negative control group, P \u0026lt; 0.0001)\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4911449/v1/9117884af0db06197135e68e.png"},{"id":65252715,"identity":"929617fa-9755-42fc-b669-8a7db6d41f92","added_by":"auto","created_at":"2024-09-25 09:11:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":343144,"visible":true,"origin":"","legend":"\u003cp\u003eAssessment of the relative RNA expression of p53 molecular pathway genes in the liver tissue of male ICR mice following 28 days of neodymium nitrate administration (A. Relative RNA expression of p53 molecular pathway genes in the liver tissue of ICR mice after 28 days of neodymium nitrate administration, B. Benchmark Dose (BMD) values for ATM content in the liver tissue of ICR mice, C. Benchmark Dose (BMD) values for Wip1 content in the liver tissue of ICR mice, D. Benchmark Dose (BMD) values for ATR content in the liver tissue of ICR mice, E. Benchmark Dose (BMD) values for MDM2 content in the liver tissue of ICR mice, F. Benchmark Dose (BMD) values for p53 content in the liver tissue of ICR mice, G. Benchmark Dose (BMD) values for p21 content in the liver tissue of ICR mice, H. Benchmark Dose (BMD) values for NF-kB content in the liver tissue of ICR mice, I. Benchmark Dose (BMD) values for Chk2 content in the liver tissue of ICR mice).\u003c/p\u003e\n\u003cp\u003e(*: Compared with the negative control group, P \u0026lt; 0.05; **: Compared with the negative control group, P \u0026lt; 0.01; ***: Compared with the negative control group, P \u0026lt; 0.001; ****: Compared with the negative control group, P \u0026lt; 0.0001)\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4911449/v1/d254db965214afa28d391eb2.png"},{"id":65252710,"identity":"4e9463cc-bd5e-4407-869c-b99e5d14b787","added_by":"auto","created_at":"2024-09-25 09:11:36","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":239152,"visible":true,"origin":"","legend":"\u003cp\u003eThe possible mechanisms of the genotoxic effects of neodymium nitrate on mouse liver\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4911449/v1/e99a20c0447d3627497405f9.png"},{"id":66342746,"identity":"282035e1-8c7f-49d5-a92e-0b3e274ff774","added_by":"auto","created_at":"2024-10-10 16:02:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1852927,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4911449/v1/79998085-6ee4-4965-81bd-40e135ce19a9.pdf"},{"id":65252712,"identity":"d5dc33b0-5a04-44f0-a35a-ba824fadd69e","added_by":"auto","created_at":"2024-09-25 09:11:36","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":10735,"visible":true,"origin":"","legend":"","description":"","filename":"Highlights.docx","url":"https://assets-eu.researchsquare.com/files/rs-4911449/v1/56154974e80d9554e3971440.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Quantitative Study on Hepatic Genotoxicity of Neodymium and Its Molecular Mechanisms Based on Benchmark Dose Method","fulltext":[{"header":"1.1 Introduction","content":"\u003cp\u003eRare earth elements (REEs) encompass the 17 elements of the lanthanide series, including lanthanum, cerium, praseodymium, neodymium (Nd), and others, with scandium and yttrium often included due to their similar chemical properties. Their unique physical and chemical attributes, such as high reactivity and low ignition points, have led to broad applications across various sectors, including industry, agriculture, medicine, and high-tech fields [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] (US EPA, 2012). Notably, REEs are integral to the production of glass, ceramics, magnets, electronics, superconductors, and lasers, with neodymium's role in manufacturing magnets for speakers, computer hard drives, wind turbines, and hybrid vehicles being particularly significant [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] (Kyung et al., 2013; Hirano et al., 1996). Additionally, fertilizers enriched with lanthanum, cerium, and neodymium have been reported to boost crop yields in China [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] (Hu et al., 2004; Ni, 2002).\u003c/p\u003e \u003cp\u003eHowever, the surge in REE mining and industrial use has resulted in their widespread release into the environment, raising concerns about potential accumulation and pollution in soil, vegetation, water, and air [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] (Huang, 2019). Neodymium, detected as the third most abundant REE in Chinese soil with a background value of 25.1 mg/kg, follows cerium at 64.7 mg/kg and lanthanum at 37.4 mg/kg, and is considered potentially highly toxic [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] (Wang et al., 2022). This has heightened the interest in neodymium's potential benefits and the associated environmental and health risks [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] (Ma et al., 2022; Freitas, 2020).\u003c/p\u003e \u003cp\u003eHuman exposure to REEs occurs through the digestive tract, respiratory system, and skin, with detectable levels in blood, urine, and hair [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] (Zhao et al., 2011). Evidence from animal studies and occupational exposure suggests that REEs can bioaccumulate and cause damage to vital organs such as the lungs, liver, and brain [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] (Liu et al., 2008). Specifically, neodymium has been implicated in oxidative damage within hepatocytes, affecting both the nuclei and mitochondria [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] (Peili H et al., 2011). The liver, lungs, and blood are recognized as primary targets for REE-induced toxicity [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] (Sturla et al., 2021), with light REEs, including neodymium, tending to accumulate in the liver and spleen [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] (Ruan et al., 2011). Studies have also linked Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e exposure to liver tissue damage, oxidative stress, and inflammation in rats [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] (Liao et al., 2009; Gao et al., 2020; Fei et al., 2011).\u003c/p\u003e \u003cp\u003eDespite the evidence of neodymium's genotoxic potential, the underlying mechanisms and long-term health impacts remain unclear, underscoring the need for further research.\u003c/p\u003e \u003cp\u003eThis study posits that neodymium nitrate's genotoxicity may be mediated through the p53 signaling pathway, a canonical route in DNA damage response. Using the OECD-recommended in vivo comet assay, we assessed neodymium nitrate's genotoxicity and investigated the correlation between hepatic neodymium content and subacute genotoxic effects. We further explored the impact of neodymium nitrate on oxidative stress markers (ROS, 8-OHdG, γ-H2AX) and p53 pathway components to delineate the mechanism of its genotoxicity.\u003c/p\u003e \u003cp\u003eThe determination of a Point of Departure (PoD) for human health risk assessment is a critical aspect of quantitative genetic evaluation. The Benchmark Dose (BMD) approach, endorsed by the International Workshop on Genotoxicity Testing (IWGT), is a prominent method for deriving PoD thresholds [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] (MacGregor JT et al., 2015; Pottenger IH et al., 2014). The BMD is calculated using specific software and models to identify the dose at which a predetermined response level change, the benchmark response (BMR), occurs [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] (Hardy A et al., 2016; EFSA, 2018; IZADI H et al., 2012).\u003c/p\u003e \u003cp\u003eThe p53 gene, a pivotal tumor suppressor and the \"guardian of the genome,\" is central to cellular responses to DNA damage and other stressors [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] (Chen et al., 2019; Lahav et al., 2004). This study examines the role of p53 pathway components in neodymium nitrate-induced DNA damage and p53 response modulation. Adhering to OECD guidelines [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] (OECD 489, 2016), we evaluated hepatocyte DNA damage and oxidative stress markers to assess neodymium nitrate's genotoxic potential. Our research aims to innovate toxicity assessment and risk prediction methodologies, enhancing chemical risk analysis, disease surveillance, and pharmaceutical research.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003cdiv id=\"Sec3\" class=\"Section3\"\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003cdiv id=\"Sec16\" class=\"Section4\"\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section4\"\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"1.2 Materials and Methods","content":"\u003ch2\u003e1.2.1 Chemicals and Reagents\u003c/h2\u003e\u003cp\u003eNeodymium nitrate hexahydrate [Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e·6H\u003csub\u003e2\u003c/sub\u003eO] was obtained from Sigma-Aldrich with a CAS number of 16454-60-7 and a purity of 99.9%. Ethyl methanesulfonate, used as a positive control, was also sourced from a reliable chemical supplier.\u003c/p\u003e\u003ch2\u003e1.2.2 Animal Model and Treatment Regimen\u003c/h2\u003e\u003cp\u003eSix-week-old ICR mice, weighing 29 ± 5 grams, were procured from Zhejiang Weitong Lihua Experimental Animal Technology Co., Ltd (China). Thirty male mice were housed under controlled conditions with a temperature of 22 ± 2℃, relative humidity of 60 ± 5%, and a 12-hour light/dark cycle. They were provided with food and water ad libitum and allowed a 5-day acclimation period prior to the experiment. The study was approved by the International Ethics Committee on Animal Welfare, and all procedures were conducted in accordance with their guidelines.\u003c/p\u003e\u003cp\u003eThe mice were randomly assigned into seven groups: a negative control, a positive control, and five experimental groups receiving Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e at dosages of 7, 27, and 55mg/kg body weight (n = 6 per group). The dosages for the 28-day subacute toxicity study were determined based on an acute genotoxicity test using a dose of 39mg/kg for male mice. Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e was administered daily by gavage for 28 days. The negative control group received an equivalent volume of purified water, while the positive control group received ethyl methanesulfonate (200mg/kg) in purified water. Daily observations of symptoms and mortality were recorded throughout the study.\u003c/p\u003e\u003cp\u003eAt the conclusion of the treatment period, blood was collected via the retro-orbital plexus method for neodymium content analysis. Mice were euthanized by cervical dislocation, and liver samples were collected for comet assay, qRT-PCR, ELISA, and histopathological examination.\u003c/p\u003e\u003ch2\u003e1.2.3 In Vivo Comet Assay\u003c/h2\u003e\u003cp\u003eThe in vivo comet assay was performed in accordance with OECD Test Guideline 489 (OECD, 2016). Three hours post the final administration, mice were euthanized, and single liver cells were isolated from the left lateral lobe. A commercial comet assay kit (Cat. BR-0904, BIOLAB Company) was utilized for the procedure. Liver cells were embedded in low-melting agarose and subjected to lysis at 4℃ for 1 hour. Following lysis, slides were neutralized, incubated in an alkaline solution to allow DNA unwinding, and then electrophoresed. Slides were subsequently stained with Gelred, rinsed, and analyzed using a Leica DM3000 fluorescence microscope equipped with a fiber optic lamp and a ×200 magnification lens. The Comet Intelligence Analysis software was employed for scoring DNA damage by quantifying the % tail DNA in 150 cells per sample.\u003c/p\u003e\u003ch2\u003e1.2.4 Determination of Neodymium Content in Livers by ICP-MS\u003c/h2\u003e\u003cp\u003eLiver tissue samples were digested in microwave digestion tubes with 5 mL of trace metal-grade nitric acid (CNW Technologies) using a microwave digestion system. The digestion program consisted of three steps: ① 5 min at 120℃ with a 5 min hold; ② 5 min at 150℃ with a 10 min hold; ③ 5 min at 190℃ with a 20 min hold. After cooling, samples were subjected to acid removal at 120℃ for approximately 30 min, then diluted to 25.0 mL with ultrapure water (18.2 MΩ·cm, Milli-Q), and mixed thoroughly.\u003c/p\u003e\u003cp\u003eAnalysis was performed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS; Agilent 8900 ICP-MS/MS, Agilent Technologies, USA) with the following parameters: RF power 1500W, concentric nebulizer, plasma gas flow 15 L/min, nickel sampling cone/skimmer cone, carrier gas flow 0.80 L/min, sampling depth 10 mm, auxiliary gas flow 0.40 L/min, peak hopping acquisition mode, helium flow 4.3 mL/min, automatic detection mode, atomization chamber temperature 2℃, three measurement points per peak, sample lift rate 0.3 r/s, and three repetitions. Indium (50 ng/mL) served as the internal standard. The neodymium detection limit was 0.0018 ng/mL, with data expressed as nanograms per gram of fresh tissue.\u003c/p\u003e\u003ch2\u003e1.2.5 γ-H2AX Liver Content by ELISA\u003c/h2\u003e\u003cp\u003eApproximately 50 mg of liver tissue was snap-frozen in liquid nitrogen for γ-H2AX content determination using an ELISA kit (Mouse γH2AX ELISA KIT, Shanghai Enzyme Union Biotechnology Co., LTD). Liver samples were homogenized in Hank’s Balanced Salt Mixture (D-Hanks, without Ca\u003csup\u003e2+\u003c/sup\u003e and Mg\u003csup\u003e2+\u003c/sup\u003e, without phenol red, pH 7.4) and centrifuged at 2000–3000 rpm for 20 min. The supernatant was collected for immediate testing or stored at -20℃ to avoid repeated freezing and thawing. Protein content was measured by the Lowry method (Lowry et al., 1951), with triplicate analyses for each sample.\u003c/p\u003e\u003ch2\u003e1.2.6 Liver ROS Content by ELISA\u003c/h2\u003e\u003cp\u003eROS content in liver tissue was determined using a similar ELISA protocol (Mouse ROS ELISA Kit, Shanghai Enzyme-Linked Biotechnology Co., Ltd.). Samples were processed and analyzed as described for γ-H2AX, with the same conditions for homogenization, centrifugation, and storage.\u003c/p\u003e\u003ch2\u003e1.2.7 Liver 8-OHdG Content by ELISA\u003c/h2\u003e\u003cp\u003eThe content of 8-OHdG in liver tissue was measured by ELISA (Mouse 8-OHdG ELISA Kit, Shanghai Enzyme-Linked Biotechnology Co., Ltd.) following the same homogenization, centrifugation, and storage procedures as the previous assays. The protein content was determined by the Lowry method, and triplicate analyses were conducted for each sample.\u003c/p\u003e\u003ch2\u003e1.2.8 cDNA Sample Preparation from Mouse Liver\u003c/h2\u003e\u003cp\u003eTotal RNA was extracted using the Total RNA Extraction Kit (TIANGEN BIOTECH, DP451, Item number: 4992562, Lot number: Y1209). The purity of RNA was confirmed with an A260/A280 ratio of 2.1, indicating sufficient freedom from protein contamination. Reverse transcription was performed using the FastKing gDNA Dispelling RT SuperMix (TIANGEN BIOTECH, KR118-02, Lot number: X1010). The resulting cDNA was resuspended in Tris-HCl buffer (pH 7.2) and stored at 4°C. mRNA expression levels were determined by qRT-PCR with the SuperReal PreMix Plus (SYBR Green, TIANGEN BIOTECH, FP205-02, Lot number: X1018), using β-actin as an internal control. Primer sequences were identified through a literature search [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] (Qin Luo et al., 2018) and synthesized by Sangon Biotech. Primer details are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrimer Pairs Used for Gene Expression Analysis by qRT-PCR\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene Name\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimer Sequence(5'\u0026nbsp;to\u0026nbsp;3')\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBase Pair Count\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProvide Total Quantity(OD)\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePurification Method\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eATM gene\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCAAGATGGCAGTGAACCAGAC-F;\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2OD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHPLC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATGCTGGACAGCTATGGTGGAG-R;\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2OD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHPLC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWip1 gene\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTCACAGTGGACCTGTCAGAAGG-F;\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2OD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHPLC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAGAGTGTGGACACTGGTGTCTG-R;\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2OD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHPLC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eATR gene\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGAAAGAGGCTCCTACCAACGAG-F;\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2OD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHPLC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCAACTGTCACCTGGAGACTTGC-R;\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2OD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHPLC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChek2 gene\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGAGGTTCTTGTCTCCAACGGGA-F;\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2OD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHPLC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATCCTTCAGGGACACTTGGGTC-R;\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2OD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHPLC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMDM2 gene\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCGAGTTTCTCTGTGAAGGAGC-F;\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2OD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHPLC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGTCTGCTCTCACTCAGCGATGT-R;\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2OD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHPLC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eβ-actin gene\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCATTGCTGACAGGATGCAGAAGG-F;\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2OD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHPLC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTGCTGGAAGGTGGACAGTGAGG-R;\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2OD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHPLC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep53 gene\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAGAGACCGCCGTACAGAAGA-F;\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2OD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHPLC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGCATGGGCATCCTTTAACTC-R;\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2OD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHPLC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep21 gene\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTCGCTGTCTTGCACTCTGGTGT-F;\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2OD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHPLC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCAATCTGCGCTTGGAGTGATAG-R;\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2OD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHPLC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNF-kB gene\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTCCTGTTCGAGTCTCCATGCAG-F;\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2OD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHPLC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGGTCTCATAGGTCCTTTTGCGC-R;\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2OD\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHPLC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003e1.2.9 Expression Analysis of p53 Pathway-Related Genes\u003c/h2\u003e\u003cp\u003eThe mRNA expression levels of ATM, Wip1, ATR, Chk2, MDM2, p53, p21, caspase3, and NF-kB were quantified by qRT-PCR. Liver samples from mice of the same growth phase, with or without Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e treatment, were homogenized, and total RNA was isolated using the aforementioned RNA extraction kit. The FastKing gDNA Dispelling RT SuperMix was used for cDNA synthesis under the following conditions: 42℃ for 15 min, followed by 95℃ for 3 min. Primers for qRT-PCR were designed using Primer Express Software and synthesized by Sangon Biotech (China). The qRT-PCR reaction mixture was prepared with SuperReal Premix Plus and consisted of a three-step cycling program: 95℃for 15 min, followed by 40 cycles of 95℃ for 10 s, 58℃ for 20 s, and 72℃ for 30 s. Gene expression analysis was conducted using standard curve and quantitation methods.\u003c/p\u003e\u003ch2\u003e1.2.10 Statistical Analysis\u003c/h2\u003e\u003cp\u003eData were analyzed using GraphPad Prism 8 and presented as means ± standard error (SE). One-way ANOVA was used to assess differences among multiple groups, followed by Tukey's HSD for pairwise comparisons with the control group, with significance set at p \u0026lt; 0.05.\u003c/p\u003e\u003cp\u003eFor the Benchmark Dose (BMD) analysis, we utilized the e(BMD) model with Benchmark Dose Software (BMDS, version 3.2) following USEPA guidance. The best-fit model was selected based on the lowest Akaike Information Criterion (AIC) to calculate parameters such as BMD, BMDL, and BMDU, representing the BMD and its 95% confidence intervals. The BMD\u003csub\u003e50\u003c/sub\u003e was used for all analyses, corresponding to a 50% increase in genotoxicity test frequency over background. Data were batched by exposure route and analyzed using combined covariate BMD modeling to ensure consistency and computational feasibility. The Index and Hill model family, recommended by EFSA for continuous data analysis, were applied. Covariate analysis assumed constant model parameters for maximum response and steepness of the dose-response curve. Unique identifiers were assigned to datasets with different parameters, used as covariates for background response, efficacy, and within-group variance. For compounds with multiple datasets, the lowest BMDL value was used for MOE calculations.\u003c/p\u003e"},{"header":"1.3 Result","content":"\u003ch2\u003e1.3.1 Effect of 28-Day Neodymium Nitrate Administration on Body Weight of ICR Mice\u003c/h2\u003e\n\u003cp\u003eThe weekly body weight changes of ICR mice following 28 days of continuous Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e administration are depicted in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e-A. No significant differences in body weight were observed between the treatment groups and the solvent control group (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). There were no noticeable changes in the general health of the treatment groups compared to the control group. Post-administration, some individual mice exhibited signs of lethargy, reduced mobility, and dulled fur; however, these symptoms did not present a consistent pattern.\u003c/p\u003e\n\u003ch2\u003e1.3.2 Determination of Neodymium Content in the Liver of ICR Mice After 28 Days of Administration\u003c/h2\u003e\n\u003ch2\u003e1.3.2.1 Limit of Detection (LOD) and Limit of Quantitation (LOQ)\u003c/h2\u003e\n\u003cp\u003eThe method\u0026apos;s detection limit was established at 0.0018 \u0026micro;g/L based on the mean response plus three times the standard deviation of 11 blank samples\u0026apos; responses. Recovery rates were between 97.2% and 111.0%, and relative standard deviations ranged from 1.63\u0026ndash;7.93%.\u003c/p\u003e\n\u003cp\u003eThe inductively coupled plasma mass spectrometer was calibrated using a mass spectrometry tuning solution to ensure optimal performance. A 10.0 \u0026micro;g/mL neodymium (Nd) standard stock solution was serially diluted with 1% nitric acid to create a calibration range of 0.05, 0.1, 0.5, and 1.0 \u0026micro;g/L. Indium (In) served as the internal standard. A calibration curve was generated with the y-axis representing the ratio of the signal values of neodymium to indium and the x-axis representing the neodymium content. The linear correlation coefficient was 0.9993, indicating that the method\u0026apos;s performance meets the detection criteria.\u003c/p\u003e\n\u003ch2\u003e1.3.2.2 Determination of Neodymium Content in the Liver of ICR Mice\u003c/h2\u003e\n\u003cp\u003eAfter continuous administration of Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e for 28 days, the changes in neodymium content in the tissues and organs of ICR mice are shown in Figs. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e-B and C. It can be observed that: In liver, it began to significantly exceed the solvent control group from a dosage of 14 mg/kg body weight (P values were 0.0008, 0.0003, \u0026lt;\u0026thinsp;0.0001, and \u0026lt;\u0026thinsp;0.0001). In hepatocytes, the neodymium content in male mice, it began to significantly exceed the solvent control group from a dosage of 39 mg/kg body weight (P values were 0.0119 and \u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e\n\u003ch2\u003e1.3.3 DNA Damage in Liver Tissue Cells Induced by 28-Day Neodymium Nitrate Administration\u003c/h2\u003e\n\u003cp\u003eIn the neodymium nitrate treatment groups, DNA breaks were observed, characterized by the presence of orange-red fluorescent nuclei and comet-shaped tails in the cells. At a treatment concentration of 55 mg/kg body weight (BW), the percentage of tail DNA content in liver cells of ICR mice was significantly increased compared to the control group, with a statistically significant difference (P\u0026thinsp;=\u0026thinsp;0.0003). Similarly, in the positive control group treated with Ethyl Methanesulfonate (EMS) at a dose of 200 mg/kg BW, the percentage of tail DNA content in liver cells of male ICR mice was significantly higher than that of the control group (P\u0026thinsp;=\u0026thinsp;0.0003), as shown in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e-D. A dose-response relationship was observed as the treatment dosage of neodymium nitrate increased, with a continuous rise in the percentage of tail DNA content in mouse liver cells. The Benchmark Dose Lower Limit (BMDL) for the percentage of tail DNA content in liver cells of male ICR mice was 17.32 mg/kg, and the Benchmark Dose (BMD) value was 31.63 mg/kg, as depicted in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e-E.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.3.4 Correlation Analysis of Neodymium Content in Liver and Liver Cells After 28 Days of Neodymium Nitrate Administration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe neodymium content in the blood and the dosage of administration showed significant correlations with all assessed indicators (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Notably, the percentage of DNA content in the tail of liver cells correlated significantly with both the neodymium content in the liver and the liver cells (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). As shown in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e-F.\u003c/p\u003e\n\u003ch2\u003e1.3.5 Effects of 28-Day Neodymium Nitrate Administration on Liver Tissue Biomarkers\u003c/h2\u003e\n\u003cp\u003e\u0026gamma;-H2AX Content:\u003c/p\u003e\n\u003cp\u003eAt a dosing concentration of 55 mg/kg body weight (BW), the liver tissue \u0026gamma;-H2AX content in male ICR mice was significantly elevated compared to the control group (P\u0026thinsp;=\u0026thinsp;0.0345). In the positive control group administered Ethyl Methanesulfonate (EMS) at 200 mg/kg BW, the \u0026gamma;-H2AX content was also significantly higher than in the control group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). As shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e-A. An increase in \u0026gamma;-H2AX content with dose escalation was observed, indicating a clear dose-response relationship. The Benchmark Dose Lower Limit (BMDL) for \u0026gamma;-H2AX content in liver tissue of male ICR mice was 20.74 mg/kg, with a Benchmark Dose (BMD) of 34.40 mg/kg. As depicted in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e-D.\u003c/p\u003e\n\u003cp\u003eROS Content:\u003c/p\u003e\n\u003cp\u003eAt dosing concentrations of 14, 39, and 55 mg/kg BW, the liver tissue ROS content in male ICR mice was significantly higher than in the control group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 for all doses). In the EMS positive control group at 200 mg/kg BW, ROS content was also significantly increased compared to the control group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). As shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e-B. A dose-response relationship was evident as the dosing concentration of neodymium nitrate increased. The BMDL for ROS content in liver tissue was 18.32 mg/kg, and the BMD was 24.21 mg/kg. As shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e-E.\u003c/p\u003e\n\u003ch3\u003e8-OHdG Content:\u003c/h3\u003e\n\u003cp\u003eAt a dosing concentration of 55 mg/kg BW, the liver tissue 8-OHdG content in male ICR mice was significantly higher than in the control group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Similarly, in the EMS positive control group at 200 mg/kg BW, the 8-OHdG content was significantly elevated compared to the control group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). As shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e-C. An increase in 8-OHdG content with dose escalation was observed, consistent with a dose-response relationship. The BMDL for 8-OHdG content in liver tissue was 20.51 mg/kg, with a BMD of 29.90 mg/kg. As shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e-F.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003e1.3.6 Effects of 28-Day Neodymium Nitrate Administration on the Relative RNA Expression of p53 Pathway Genes in Liver Tissue of Male ICR Mice\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eRNA extraction was performed using the Tiangen Animal Tissue and Cell Total RNA Extraction Kit (DP451) following the manufacturer\u0026apos;s protocol. Reverse transcription was conducted using the Tiangen One-Step gDNA Removal cDNA Synthesis Kit (KR118). Quantitative real-time PCR (qRT-PCR) was used to assess mRNA expression levels with the Tiangen SuperReal PreMix Plus (SYBR Green) as the fluorescent quantitative premixed reagent, using \u0026beta;-actin as the internal control. Primers were selected based on a literature search (Haiquan Zhao et al., 2012).\u003c/p\u003e\n\u003cp\u003eIn male ICR mice, the relative RNA expression of the following genes showed significant increases compared to the control group at the indicated neodymium nitrate dosing concentrations:\u003c/p\u003e\n\u003cp\u003e- ATM: At 27 and 55 mg/kg body weight (BW), with P-values of 0.0239 and 0.0004, respectively.\u003c/p\u003e\n\u003cp\u003e- Wip1: At 27 and 55 mg/kg BW, with P-values of 0.0097 and 0.0003, respectively.\u003c/p\u003e\n\u003cp\u003e- ATR: At 27 and 55 mg/kg BW, with P-values of 0.0030 and 0.0002, respectively.\u003c/p\u003e\n\u003cp\u003e- MDM2: At 27 and 55 mg/kg BW, with P-values of 0.0004 and \u0026lt;\u0026thinsp;0.0001, respectively.\u003c/p\u003e\n\u003cp\u003e- p53: At 7 and 27 mg/kg BW, with P-values of 0.0019 and 0.0379, respectively.\u003c/p\u003e\n\u003cp\u003e- p21: At 7, 27, and 55 mg/kg BW, with P-values of 0.0464, 0.0070, and 0.0005, respectively.\u003c/p\u003e\n\u003cp\u003e- NF-kB: At 7, 27, and 55 mg/kg BW, with P-values of 0.0310, 0.0020, and \u0026lt;\u0026thinsp;0.0001, respectively.\u003c/p\u003e\n\u003cp\u003e- Chk2: At 27 and 55 mg/kg BW, with P-values of 0.0065 and \u0026lt;\u0026thinsp;0.0001, respectively.\u003c/p\u003e\n\u003cp\u003eAll observed differences were statistically significant, indicating a dose-dependent effect of neodymium nitrate on the expression of these genes. As shown in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e-A. BMD calculations for the relative RNA expression of p53 pathway genes in the liver tissue of male ICR mice after 28 days of neodymium nitrate administration were performed, and the BMD values for each gene in the p53 pathway are depicted in Figs. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e-B, C, D, E, F, G, H, and I. A summary of the BMD values for the genes in the p53 pathway is presented in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBMD Calculation for qPCR Quantitative Analysis\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep53 Molecular Pathway Gene\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBMD(mg/kg)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBMDL(mg/kg)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eATM gene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWip1 gene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eATR gene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMDM2 gene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep53 gene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep21 gene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNF-kB gene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChK2 gene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e"},{"header":"1.4 Discussion","content":"\u003cp\u003eTraditional genotoxicity testing paradigms, established in the 1970s and 1980s in North America, Japan, and Europe, have been pivotal in dichotomously classifying chemicals as genotoxic or non-genotoxic. This binary categorization has underpinned risk management strategies for decades. However, the advent of high-throughput testing technologies has unveiled complex, non-linear dose-response relationships, particularly at low doses. Aneugens like colchicine and mutagenic substances such as methyl sulfonate demonstrate curved dose-response patterns, suggesting that biological responses to these agents may entail both dose-dependent and threshold mechanisms. These insights necessitate a reevaluation of existing models and a more nuanced understanding of dose-response dynamics, especially at lower exposure levels, to accurately assess chemical safety and potential human health risks.\u003c/p\u003e\u003cp\u003eQuantitative genotoxicity risk assessment has advanced beyond qualitative methods, offering a more refined tool for evaluating health risks. The traditional ALARA principle has been augmented by quantitative approaches that calculate the margin of exposure (MOE), the ratio of acceptable exposure levels to actual or anticipated human exposure. This metric facilitates a more precise estimation of health risks associated with genotoxicants. Quantified measures like MOEs and reference doses enhance the ability of risk managers to prioritize and control genotoxic substances effectively and communicate the magnitude of risks to the public and policymakers.\u003c/p\u003e\u003cp\u003eIn this study, 28 days of continuous neodymium nitrate (Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e) administration to ICR mice revealed no significant body weight changes compared to the control group, suggesting minimal toxicity within the tested dosage range (7–55 mg/kg for males). ICP-MS analysis indicated liver accumulation of neodymium, highlighting the liver as a primary target organ.\u003c/p\u003e\u003cp\u003eOur findings indicate potential genotoxic effects of Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e in mice, with implications for human exposure. Hepatocyte alkaline comet assays were conducted in accordance with OECD guidelines, providing precise DNA damage measurements. A quantitative genotoxicity assessment using the Benchmark Dose (BMD) approach allowed us to calculate the MOE for human health risks, offering a comprehensive evaluation of Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e genotoxicity.\u003c/p\u003e\u003cp\u003eCorrelation analysis between liver neodymium concentration and genotoxicity outcomes post-Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e administration revealed significant associations, suggesting a dose-dependent genotoxic effect. The biomarker analysis further confirmed Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e-induced genotoxicity and its DNA damaging effects on hepatocytes.\u003c/p\u003e\u003cp\u003eThe p53 signaling pathway, a critical biomarker in genotoxicity research, was examined for its role in the molecular response to Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e. Our analysis of BMD (Benchmark Dose) and BMDL (Benchmark Dose Lower Limit) values for genes in the p53 pathway, including ATM, Wip1, ATR, MDM2, p53, p21, NF-κB, and Chk2, along with comet assay and genotoxicity biomarker data, identified p21, MDM2, and Wip1 as potential early indicators of DNA damage. These findings provide a theoretical foundation for understanding the genotoxicity mechanism of Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eAs a cyclin-dependent kinase inhibitor, p21 is intricately linked to tumor suppression, regulating cell cycle, DNA replication, and repair processes. qRT-PCR analysis of the p53 pathway and downstream genes revealed significant upregulation of ATM, ATR, Wip1, MDM2, p21, and Chk2, suggesting a close relationship between Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e-induced liver genotoxicity and the p53 pathway, with implications for cell cycle arrest.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAll experiments involving live vertebrates were conducted in accordance with the guidelines and regulations set forth by the Shanghai Center for Disease Control and Prevention \u0026amp; Shanghai Institute of Preventive Medicine of the Institutional Animal Care and Use Committee (IACUC). The study was approved by the Shanghai Center for Disease Control and Prevention \u0026amp; Shanghai Institute of Preventive Medicine, with the approval number KY20230002. All efforts were made to minimize animal suffering and to reduce the number of animals used for the experiments. The ARRIVE guidelines (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://arriveguidelines.org\u003c/span\u003e\u003c/span\u003e) were followed to ensure the comprehensive and transparent reporting of the methods and results of the animal experiments.\u003c/p\u003e\n\u003ch2\u003eConflict of Interests\u003c/h2\u003e\n\u003cp\u003eWe declare no conflict of interests.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eThe primary manuscript text was written by Ning Wang, Xiu-li Chang, Jing Leng, Xin-yu Hong, and Xu-dong Jia. Figures 1 to 3 were completed by Xue-qing Cheng, Yu Ding, Jing Xu, Zhengli Yang, Hui-min Zhang, and Jing-qiu Sun. All authors have reviewed the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eThis work was supported by the Food Toxicology Program, of the National Center for Food Safety Risk Assessment.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003ewe have uploaded the data to the OMIX repository, with the accession number: OMIX007180, and have added a data availability statement at the end of the manuscript in section 1.7.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBarlow S., et al., Risk assessment of substances that are both genotoxic and carcinogenic report of an International Conference organized by EFSA and WHO with support of ILSI Europe. Food Chem Toxicol, 2006, 44(10):1636-1650.\u003c/li\u003e\n\u003cli\u003eCao XF., et al., Quantitative dose-response analysis of ethyl nethanesulfonate genotoxicity in adult gpt-delta trangenic mice. 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(2017), Comparing BMD-derived genotoxic potency estimations across variants of the transgenic rodent gene mutation assay. Environmental and Molecular Mutagenesis, 58, 632\u0026ndash;643.\u003c/li\u003e\n\u003cli\u003eZeller A., et al., A proposal for a novel rationale for critical effect size in dose-response analysis based on a multi-endpoint in vivo study with methyl methanesulfonate. Mutagenesis, 2016,31(3):239-253\u003c/li\u003e\n\u003cli\u003eZhang XY., et al., Progress in p53-independent signaling in DNA damage-induced apoptosis. Journal of Zhejiang University (Medical edition), 2013,42 (2): 217-223.\u003c/li\u003e\n\u003cli\u003eZhao, H., et al., Oxidative injury in the brain of mice caused by lanthanid. Biol Trace Elem Res, 2011. 142(2): 174-89.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4911449/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4911449/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNeodymium has been shown to induce genotoxicity in mice, but the molecular mechanisms behind this effect are not fully understood. To clarify the genotoxic effects of intragastric neodymium nitrate (Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e) administration over 28 consecutive days, we assessed the percentage of tail DNA in mouse hepatocytes using the alkaline comet assay, genetic toxicological biomarkers, and the expression levels of genes and proteins related to the p53 pathway in the mouse liver. Our results indicated significant accumulation of Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e in the livers and kidneys of mice, resulting in micronuclei formation and DNA double-strand breaks, as indicated by comet and γ-H2AX assays, as well as DNA damage in hepatocytes. Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e significantly increased the percentage of tail DNA in hepatocytes as measured by the alkaline comet assay and upregulated the expression of p53 pathway-related molecules, including ATM, Wip1, ATR, Chk2, MDM2, p53, p21, and NF-kB, at both the transcriptional and translational levels. This treatment effectively triggered the production of reactive oxygen species (ROS), 8-hydroxy-2'-deoxyguanosine (8-OHdG), and γ-H2AX in liver tissue. These findings suggest that Nd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e induces hepatic genotoxicity and injury in mice, and modulates the expression of genes associated with DNA damage response, carcinogenesis, and inflammatory processes.\u003c/p\u003e","manuscriptTitle":"Quantitative Study on Hepatic Genotoxicity of Neodymium and Its Molecular Mechanisms Based on Benchmark Dose Method","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-25 09:11:31","doi":"10.21203/rs.3.rs-4911449/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"949fd964-fd0b-4567-aaaf-fa2ddeb303c5","owner":[],"postedDate":"September 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":37227253,"name":"Health sciences/Medical research"},{"id":37227254,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2024-10-10T15:53:55+00:00","versionOfRecord":[],"versionCreatedAt":"2024-09-25 09:11:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4911449","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4911449","identity":"rs-4911449","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}