Method for identifying and tracing toxic metal components in indoor dust

Abstract

The invention belongs to the technical field of toxic metal component identification, and particularly relates to a method for identifying and tracing toxic metal components in indoor dust. The technical problem to be solved is to solve the problem that in the process of distinguishing specific metal elements in a body, the source of the metal elements is difficult to distinguish due to the problem of interference between the complexity of metal components in complex particulate matters and a metal metabolism background in an organism. According to the core means, the isotope ratio of iron in lung tissue and dust is identified to confirm the homology, and whether iron elements accumulated in biological samples come from exogenous iron introduced by indoor dust exposure or not is judged by comparing the closeness degree of the isotope ratio between the biological samples of a control group and an exposure group and particulate matter. Source judgment: distinguishing the exposure input of metal accumulation from in-vivo metabolic disorder or exogenous particulate matters; the method can be popularized to screening of effect components of health outcomes such as respiratory system toxicity and cardiovascular toxicity.

Description

Technical Field

[0001] The present invention belongs to the technical field of identification of toxic metal components, and particularly relates to a method for identifying and tracing toxic metal components in indoor dust. Background Art

[0002] More than 90% of a human's life is spent indoors, and the quality of the air inhaled by the body accounts for nearly 90% of the total mass inhaled. The safety of indoor air is very important for the health of the population. In the 1970s, some developed countries had indoor air quality problems. Researchers found that the disability-adjusted life year loss caused by the chronic hazards it triggered was about 400 - 1100 DALYs / year per 100,000 people. In China, in the past 20-odd years, it has experienced a rapid urbanization process and economic development. The pollutions that occurred in developed countries over half a century have almost simultaneously and concentratively emerged in China. Coupled with some unique reasons such as the large-scale use of artificial composite materials and products in the indoor environment, it faces more severe and complex health hazards. Epidemiological studies show that there is a statistical correlation between indoor air pollution and human health risks, which causes about 4.5 million deaths globally every year from diseases such as pneumonia (12%), stroke (34%), ischemic heart disease (26%), chronic obstructive pulmonary disease (22%), and lung cancer (6%).

[0003] As a reaction medium and attachment carrier for various pollutants, dust particles are considered an important matrix for exploring indoor environmental air pollution. Currently, it has been confirmed that they include components such as heavy metals, phthalates, bromine / phosphorus flame retardants, harmful microorganisms and their derivatives. Among them, the loaded metal components are important contributors to toxic effects. However, there are multiple metal element metabolism systems in the organism itself (such as the iron metabolism system), resulting in background interference. Currently, there is a lack of an effective method for tracing back from the toxic effects of the organism after dust exposure to external metal elements.

[0004] As is well known, the human body produces approximately 150 million red blood cells per minute to maintain a stable state level and prevent the development of anemia. Erythropoiesis refers to the production of red blood cells, which highly depends on iron (Fe). Hemoglobin contains Fe element (Fe 2+ ), and it is an important carrier substance for transporting oxygen. The iron in heme is divalent. When combined with oxygen, its chemical valence remains unchanged, forming oxyhemoglobin, which is bright red. After dissociating from oxygen, it is light blue. One of the important factors of anemia is iron deficiency, which can lead to iron deficiency anemia. The reason is the disorder of iron element absorption, resulting in the malfunction of hemoglobin.

[0005] On the contrary, excessive iron can disrupt the proliferation of erythroid progenitor cells in the bone marrow and impair the hematopoietic function of the erythroid series. Therefore, a lack of hemoglobin does not necessarily mean a low iron content in the body, but is caused by various factors. The sources of iron include not only food but also metal particles in the air, which enter the body through respiration. For example, when we explored the hematotoxicity of dust, we found that indoor dust can cause anemia in mice. Further omics analysis revealed that abnormal erythrocyte development may be caused by iron metabolism disorders.

[0006] Therefore, by detecting iron metabolism-related proteins and combining histochemical staining techniques, such as the traditional Prussian blue staining, it can be found that there is iron overload in the mouse body, which is associated with abnormal erythrocyte development caused by iron metabolism disorders. However, traditional techniques are difficult to distinguish whether the iron accumulated in the body is due to internal disorders or external input. An effective and accurate means of tracing iron elements in the body is needed to achieve the goal of preventing and improving the iron content in the body. Summary of the Invention

[0007] The technical problem to be solved by the present invention is that during the process of distinguishing specific metal elements in the body, it is difficult to distinguish the source of metal elements due to the complexity of metal components in complex particles and the interference of the metal metabolism background in the organism.

[0008] The present invention proposes a method for identifying and tracing toxic metal components in indoor dust. Further, a method for identifying and tracing toxic metal components in indoor dust with a toxic mechanism in the body, which combines toxicological mechanism analysis and stable isotope ratio analysis, is proposed to achieve the following goals: Precise screening: Identify effector metal elements related to specific health outcomes (such as anemia) from complex particles; Source determination: Distinguish whether metal accumulation is due to internal metabolic disorders or exogenous particle exposure input; Universal application: Can be extended to the screening of effector components for health outcomes such as respiratory toxicity and cardiovascular toxicity.

[0009] The technical solution to achieve the present invention is a method for identifying and tracing toxic metal components in indoor dust, including the following steps: 1. Construct a health endpoint model with anemia as the effect endpoint. 2. Omics-driven mechanism analysis: Screen out the toxic metal component - iron element based on transcriptome sequencing of the hematopoietic organ bone marrow. 3. Verification of iron metabolism disorders: Use enzyme-linked immunosorbent assay and histochemical staining methods to verify iron metabolism-related proteins to verify iron metabolism disorders. 4. Tracing iron elements by combining multiple techniques: Transmission electron microscopy was used to observe the deposition of dust particles in lung tissues, inductively coupled plasma mass spectrometry (ICP-MS) was used to quantify iron accumulation, and finally, multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) was used to examine the iron isotope ratios in lung tissues and dust to confirm their homology, thereby determining whether the iron elements accumulated in the body were exogenous iron introduced by indoor dust exposure.

[0010] In the tracing stage, transmission electron microscopy (TEM) was first used to determine the deposition of particulate matter, then inductively coupled plasma mass spectrometry (ICP-MS), a chemical method, was used to quantify the increase in iron in tissues, and finally, multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) was used to detect the iron isotope ratios in tissues and particulate matter for source determination of iron elements. It was found that the iron elements accumulated in the exposed group came from particulate matter outside the body. High-precision MC-ICP-MS can be used as an important tool for identifying the homology of metal elements in biological organisms and exposure sources. Its basic principle is to judge whether the iron elements accumulated in biological samples come from particulate matter by comparing the proximity of isotope ratios between control group and exposed group biological samples and particulate matter.

[0011] Furthermore, the core process of the present invention includes the following four stages (taking anemia as an example): A method for identifying and tracing toxic metal components in indoor dust, the steps include: Step 1: Construction of a health endpoint model: Establish a mouse model of indoor dust exposure, and confirm the anemia phenotype through blood routine tests (hemoglobin, red blood cell count) and bone marrow pathological analysis; Step 2: Omics-driven mechanism analysis: Perform transcriptome sequencing on bone marrow tissues, screen differentially expressed genes (DEGs), and lock the ferroptosis pathway and iron ion binding-related biological processes through KEGG / GO enrichment analysis; Step 3: Verification of iron metabolism disorder: Use ELISA to quantify serum hepcidin (Hepcidin), ferritin (FE), etc., and transferrin receptor (TFRC) in lung and bone marrow tissues, etc., and combine Prussian blue staining to localize iron deposition in lung and bone marrow organs.

[0012] Step 4: Tracing iron elements by combining multiple techniques: TEM electron microscopy: Observe the ultrastructure of the lung to determine the deposition of particulate matter; ICP-MS: Detect the iron content (mg / g) in lung tissues to quantify the accumulation of iron elements; MC-ICP-MS: Determine δ 56 Fe isotope ratio to determine the homology of lung iron and dust iron; In step 4, TEM electron microscopy was used to examine the deposition of particulate matter. Specifically, lung tissues of mice in different groups were collected (tissue size less than 2 mm3 Stored in 2.5% glutaraldehyde (Sigma). After at least 24 hours, the samples were dehydrated and then fixed with 1% osmium tetroxide solution (SPI-Chem). After dehydration with ethanol, the specimens were embedded in epoxy resin, cut into ultrathin sections, and then stained with 2% uranyl acetate (SPI-Chem) and 3% lead citrate. Finally, the ultrastructure of mouse lungs was examined using a transmission electron microscope (JEM 1400, JEOL) to observe whether there was particulate matter deposition in the lung tissue.

[0013] For the determination of iron element by ICP-MS in Step 4, specifically: dry dust, control group lungs, and the 25 mg / kg body weight dust exposure group were placed in a digestion cell, 9 mL of nitric acid was added, and pretreatment was carried out at 120 °C for 30 min. Subsequently, the samples were removed, 1 mL of nitric acid and 1 mL of hydrogen peroxide were added in a microwave oven. The temperature and time gradient were set to heat at 150 °C for 10 min, then at 180 °C for 5 min, and then the temperature was maintained at 200 °C for 30 min. After the microwave cycle was completed, the mixture was acidified to approximately 2 - 3 mL at 170 °C using an acidifier, then cooled, and the volume was adjusted. The iron content was determined using an inductively coupled plasma-mass spectrometer ICP-MS instrument.

[0014] For the determination of iron element by MC-ICP-MS in Step 4, specifically: Dry dust, control group lungs, and the 25 mg / kg body weight dust exposure group were placed in a digestion cell, 9 mL of nitric acid was added, and pretreatment was carried out at 120 °C for 30 min. Subsequently, the samples were removed, 1 mL of nitric acid and 1 mL of hydrogen peroxide were added in a microwave oven. The temperature and time gradient were set to heat at 150 °C for 10 min, then at 180 °C for 5 min, and then the temperature was maintained at 200 °C for 30 min. After the microwave cycle was completed, the mixture was acidified to approximately 2 - 3 mL at 170 °C using an acidifier, then cooled, and the volume was adjusted. The metal stable isotope analysis of iron was carried out using a multi-receiver inductively coupled plasma mass spectrometer MC-ICP-MS instrument, measured in high-resolution mode, and the isotope ratio (δ 56 Fe value) was calculated relative to the reference material IRMM-014: δ 56 Fe = [( 56 Fe / 54 Fe) sample / ( 56 Fe / 54 Fe) standard] × 10 3 Specifically, by comparing the proximity of the δ 56 Fe isotope ratios between the biological samples of the control group and the exposure group and the particulate matter to determine whether the iron element in the biological samples comes from the particulate matter. The higher the degree of proximity, the stronger the homology.

[0015] The technical solution of the present invention integrates toxicology and geochemistry across disciplines for the first time, combines the analysis of toxicological mechanisms (such as screening the ferroptosis pathway by transcriptome sequencing) with the stable isotope ratio technology in the field of geochemistry (determining δ 56 Fe by MC-ICP-MS), breaks through the limitations of traditional single-discipline methods, and realizes the whole-process research of "from toxicity mechanism to exposure source tracing". A collaborative analysis process of TEM (observation of particle deposition), ICP-MS (metal quantification), and MC-ICP-MS (isotope tracing) is constructed to conduct morphological determination, quantitative analysis, and source determination of toxic metal components. The method is universal, and the health endpoints are scalable, and it can be extended and applied to the screening of toxic metal components for other health outcomes (such as respiratory toxicity, neurotoxicity, cardiovascular toxicity) of various complex particles (such as indoor dust, PM2.5, industrial dust).

[0016] This method can be used for screening toxic metal components in complex particles, solves the difficulty of identifying effective components in complex particles, and can effectively associate health effects with components. Regarding the screening and tracing method of metal components in indoor dust, it combines toxicological experiments and isotope detection techniques. Especially for the anemia effect, iron elements are screened and the sources are confirmed by isotope ratio analysis. The innovation lies in the combination of multiple technologies, which solves the problem that traditional methods cannot distinguish the sources of metals in vivo and in vitro.

[0017] Compared with the prior art, the beneficial effects brought by the technical solution of the present invention are as follows: Traditional toxicological methods can only lock the metal metabolism system related to health effects, cannot clarify the relationship between the health outcomes of complex particles and the effective metal elements, especially cannot distinguish the sources of metal accumulation in organisms (such as endogenous metabolic disorders or exogenous particle input). Single isotope tracing cannot simulate the authenticity of complex particle exposure. However, the present invention realizes the accurate determination of the in vivo and in vitro sources of metal elements for the first time by combining stable isotope ratio analysis (MC-ICP-MS) (such as determining by the difference in δ 56 Fe isotope fingerprints), filling the technical gap in metal tracing in complex particle exposure research. The technical framework established by the present invention, which is based on specific health outcomes, uses toxicological means to lock toxic metal components and combines multiple technologies of TEM—ICP-MS—MC-ICP-MS for tracing, can quickly adapt to the screening of toxic metal components of other complex particles by replacing the health endpoint model (such as respiratory toxicity, cardiovascular toxicity) and targeted omics analysis. Description of the Drawings

[0018] Figure 1Adverse effects of indoor dust on body weight (bw), blood parameters, and bone marrow (BM); In the figure: (A) Body weight measurements of mice at weeks 0, 1, 2, 3, and 4 of indoor dust exposure (n = 19 - 21); (B - F) Effects of indoor dust on the levels of WBCs, PLT, red blood cells, HGB, and RET. WBC represents white blood cells; PLT represents platelets; HGB represents hemoglobin; RET represents reticulocytes (n = 20 - 25); (G) Representative histological images of the femurs of control mice and indoor dust exposure groups at 5 and 25 mg / kg body weight; (H) Trabecular bone area statistics (n = 3). Data are presented as mean ± SEM. Compared with the control group, the differences were statistically significant, respectively, as ** p ≤0.05, ** p ≤0.01, *** p ≤0.001; Figure 2 Analysis of the mRNA expression profile in BM cells after dust exposure; In the figure: (A) GO enrichment analysis of downregulated DEGs. (B) KEGG chord diagram representing downregulated DEGs; Figure 3 Average fluorescence intensity of transferrin TFRC at different stages of red blood cell development; Data are presented by the mean ± SEM method (n = 7 - 10). * p ≤ value of 0.05 indicates a statistically significant difference compared with the control group; Figure 4 Effects of dust on iron metabolism; In the figure: (A) Schematic diagram of iron metabolism; (B) Serum iron (n = 14 - 15), ferritin (FE), transferrin (TF), and hepcidin levels (n = 6 - 8); (C) Contents of divalent metal transporter (DMT1), receptor transferrin (TFRC), and ferroportin (FPN) in the lung and bone marrow (BM) (n = 6 - 8); Data are presented as mean ± SEM (n = 6 - 8). Compared with the control group, the differences were statistically significant, respectively, as ** p ≤0.05, ** p ≤0.01, *** p ≤0.001; Figure 5 Tracing analysis of iron in vivo; In the figure: (A) Transmission electron microscopy of lung tissue; (B) Iron staining of bone marrow and lung tissue sections; (C) Detection of iron content in the lung by ICP - MS; (D) δ56Fe / δ57Fe values for detecting the lung iron levels of dust and lung tissue samples; (E) δ56Fe values of dust and lung tissue samples; Data are presented as mean ± SEM (n = 3). Compared with the control group, the differences were statistically significant, respectively, as ** p≤0.05, ** p ≤0.01, *** p ≤0.001. Detailed implementation manners

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Apparently, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without any creative effort fall within the scope of protection of the present invention.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the art to which the present invention belongs. The materials cited herein and the materials they cite will be incorporated by reference.

[0021] Equivalent technologies of the specific embodiments described that can be understood by those of ordinary skill in the art through conventional experiments will be included in this application.

[0022] The experimental methods in the following embodiments are all conventional methods unless otherwise specified. The instruments and equipment used in the following embodiments are all conventional laboratory instruments and equipment unless otherwise specified; the experimental materials used in the following embodiments are all obtained from conventional biochemical reagent stores unless otherwise specified.

[0023] Example 1. A method for identifying and tracing toxic metal components in indoor dust, the specific steps are as follows: 1. Collection of indoor dust samples. During the winter heating period in Taiyuan City, Shanxi Province, China, sampling points were selected in urban residences of Class I civil buildings according to the "Indoor Air Quality Standard" (GB / T 18883-2020) and the "Indoor Environmental Pollution Control Standard for Civil Building Projects" (GB 50325-2020). The sample points were placed away from transportation and industrial sources. Before sampling, each location was kept unwashed for 24 hours. Dust samples were collected indoors using a 400 W vacuum cleaner and a 500-mesh (30 μm) nylon filter bag placed on the floor and furniture surfaces. After collection, the nylon bag was washed to remove debris, and then screened with a 150-mesh (about 100 μm) nylon sieve. The filtered material was stored in a clean EP tube and kept in a refrigerator at -20°C for future analysis. The collected samples were mixed and partially prepared into suspensions with concentrations of 5 and 25 mg / mL using physiological saline for animal experiments.

[0024] 2. Establish an indoor dust exposure mouse model, animal exposure protocol, and dust treatment. All C57BL / 6J mice were obtained from Vital River Laboratory Animal Technology Co., Ltd. (Beijing, China). Considering the actual dose of population exposure, mice were instilled with 5 or 25 mg / kg of indoor dust (hereinafter referred to as dust) into the nasal cavity. The exposure dose of 5 or 25 mg / kg was used for mice every two days.

[0025] Analyze blood parameters. Blood was drawn from the orbital sinus. The counts of white blood cells (WBC), red blood cells, and platelets (PLT) were measured using a hematology analyzer (Sysmex K-4500, Sysmex Co., Kobe, Japan).

[0026] Histopathological analysis. The femurs and lungs of mice were collected and then preserved in 4% buffered paraformaldehyde phosphate. After a 24-hour fixation period, the femurs were decalcified in 10% ethylenediaminetetraacetic acid for two weeks and then further processed. The samples were embedded in paraffin and subsequently stained with hematoxylin and eosin. The bone volume fraction, expressed as B.Ar / T.Ar (%), and iron staining of femur and lung tissue sections were both performed according to the protocol provided in the BaSO iron staining kit (BaSO, Zhuhai, China). The prepared sections were qualitatively evaluated and images were acquired using a microscope (Olympus BX51, Japan).

[0027] Effects of dust on peripheral blood cells and bone marrow (BM). Dust exposure mainly occurs through inhalation, ingestion, and skin contact, among which respiratory exposure is particularly important. Therefore, during the four-week exposure period, dust was instilled into the nasal cavity. Starting from the 4th week, the body weight of mice with a dose of 5 mg / kg decreased significantly. Starting from the 3rd week, mice in the 25 mg / kg dust exposure group also experienced a similar decrease ( Figure 1 A). Compared with the control group, there was no significant effect on WBCs and PLT after exposure to dust ( Figure 1 B and C). However, the red blood cell counts in the 5 mg / kg and 25 mg / kg dust exposure groups decreased by 22.22% and 27.84% respectively, while the hemoglobin contents decreased by 16.51% and 19.75% respectively ( Figure 1 D and E). In addition, reticulocytes increased by 34.75% and 38.75% respectively (<able> Figure 1 F), indicating that dust exposure has an adverse effect on red blood cells. These results suggest that dust exposure may cause anemia in mice.

[0028] Anemia can be caused by a variety of factors, including deficiencies in nutrients such as iron, inflammation, hemoglobin synthesis disorders, and erythrocyte production or survival. Hematopoiesis in adults mainly occurs in the bone marrow, where PLT, WBCs, and mature erythrocytes are produced and then transported into the blood to meet the body's needs. To investigate potential problems in erythrocyte production, we examined pathological sections of mouse bone marrow. The results of hematoxylin and eosin showed that exposure to dust led to trabecular bone growth, a decline in hematopoietic tissue, and the occurrence of fibrosis ( Figure 1 G and H). Similarly, exposure to formaldehyde and benzene can result in a reduction in hematopoietic tissue in the mouse bone marrow and a decrease in the number of erythrocytes in the peripheral blood.

[0029] 3. Genomics-driven mechanism analysis: Bone marrow cell collection. Bone marrow cells were extracted from the femurs. The bone marrow cells were crushed with a plunger on a 70-μm cell strainer. The filtered cells were centrifuged at 400 × g for 5 min at 4°C. Mature erythrocytes were lysed with lysis buffer on ice for 5 min. To stop the lysis process, complete medium (BMEM medium supplemented with 10% fetal bovine serum and 1% penicillin-streptomycin) was used, and then the cells were resuspended in phosphate-buffered saline.

[0030] mRNA transcriptome sequencing analysis. Bone marrow cells were independently collected from the femurs of 3 mice in the control group and the 25 mg / kg body weight dust-exposed group for mRNA transcriptome sequencing, and the transcriptome sequencing was performed by NeoBiotechnology Co., Ltd. (Shanghai, China). Screening of differentially expressed genes (DEGs) between the two groups was performed using p-adj the criteria of <0.01 and |FoldChange| ≥ 1.2. Gene ontology enrichment analysis and pathway analysis of the DEGs were performed using the DAVID website.

[0031] To explore its mechanism of action, total RNA was isolated from bone marrow cells for high-throughput sequencing ( Figure 2 A and B). Functional and pathway enrichment analysis of the DEGs showed that dust exposure affected biological processes related to erythrocyte differentiation and development, as well as iron homeostasis in the bone marrow ( Figure 2 A). In addition, it also affected signaling pathways related to ferroptosis and hematopoietic cell lineages ( Figure 2 B). Given the crucial role of iron metabolism in erythrocyte development, these findings suggest that exposure to dust may disrupt erythrocyte development by altering iron metabolism, which may lead to anemia in mice.

[0032] 4. Verification of iron metabolism disorder: Flow cytometry (FCM) analysis. To analyze erythroid cells, bone marrow cells were stained with an antibody mixture consisting of CD71 (eFluor 450), CD44 (FITC), c-Kit (PE), and TER-119 (APC). In addition, a fixable viability dye (eFluor 780) was used to distinguish live cells from dead cells.

[0033] Determination of iron metabolism-related indicators. Serum iron was detected according to the protocol outlined in the serum iron concentration detection kit provided by Beijing Solarbio Science & Technology Co., Ltd. The levels of iron metabolism-related proteins were quantitatively determined by enzyme-linked immunosorbent assay (ELISA). Lung cells and bone marrow cells were collected and homogenized in ice-cold 0.1 M phosphate buffer (pH 7.4). After centrifuging the homogenate at 5000×g for 10 min, the supernatant was retained. Hepcidin, ferritin (FE), divalent metal transporter 1 (DMT1), ferroportin (FPN), transferrin receptor (TFRC), and transferrin (TF) were assayed using ELISA kits from Jianglai (Wuhan, China) according to the manufacturer's instructions.

[0034] The effect of dust on endogenous iron metabolism from the lung to the bone marrow. The cell cycle, erythroid transcription factors, external factors including certain cytokines, and the balance of iron metabolism affect erythroid development. Erythroid progenitor cells mainly internalize transferrin-bound iron (TF-Fe) through TFRC to obtain a large amount of iron for development. However, our results showed that the expression of TFRC on the surface of Pro-E, Baso-E, and Poly-E in the bone marrow of the dust-exposed group was significantly decreased at the early stage of erythroid maturation ( Figure 3 , p <0.05). This finding further suggests that abnormal iron metabolism may lead to disorders in bone marrow erythroid maturation.

[0035] Iron is crucial for hemoglobin synthesis and affects erythropoiesis. Iron deficiency anemia and iron-loaded anemia are both iron-related conditions. Systemic iron homeostasis includes absorption, transport, storage, and recycling. Fe 3+ is reduced to Fe 2+ , and is absorbed by enterocytes in the duodenum through DMT1. Similarly, the lung also has the ability to absorb iron. FPN exports Fe 2+ into the circulation, and TF transports iron to cells. Cells take up iron through DMT1 or TFRC, and excess iron is stored in FE. FPN is the main pathway for iron efflux and is regulated by hepcidin. When serum iron levels increase, the liver produces more hepcidin, which enters the blood and acts on FPN, promoting its internalization and degradation ( Figure 4 A).

[0036] To study the effect of dust on the iron metabolism system of mice, we measured the levels of serum iron and hepcidin, as well as the protein levels related to iron uptake, transport, and export. The results of this study showed that the serum ferritin level in mice exposed to dust increased, and the levels of iron and hepcidin were significantly elevated ( Figure 4 B, p <0.05). In addition, we also observed that the expression of TFRC, DMT1, and FPN decreased significantly in the lungs and bone marrow ( Figure 4 C, p <0.05). These results indicate that iron overload occurs in mice. Generally, when the proteins related to iron uptake increase, the supply and absorption of iron exceed the body's physiological needs, leading to iron overload in the body. In dust-exposed mice, the levels of iron uptake-related proteins decreased, indicating that these mice may have experienced an external influx of iron. This influx activated the iron regulatory system, resulting in the inhibition of iron uptake and the enhancement of iron excretion. However, it is necessary to further study whether the iron present in the dust is absorbed by the mice through exposure, leading to iron metabolism disorders.

[0037] 5. Tracing iron elements by combining multiple techniques: (1) Transmission electron microscopy was used to examine particulate deposition and perform ultrastructural analysis. Lung sections of mice from different groups were collected. Subsequently, these specimens were stored in 2.5% glutaraldehyde (Sigma). After at least 24 hours, the samples were dehydrated and then fixed with 1% osmium tetroxide solution (SPI-Chem). After dehydration with ethanol, the specimens were embedded in epoxy resin, cut into ultrathin sections, and then stained with 2% uranyl acetate (SPI-Chem) and 3% lead citrate. Finally, the ultrastructure of the mouse lungs was detected using a transmission electron microscope (JEM 1400, JEOL).

[0038] (2) ICP-MS was used to detect iron elements, analyze iron isotopes and concentrations. Dry dust, lungs of the control group, and the 25 mg / kg body weight dust-exposed group were placed in a digestion cell, and 9 mL of nitric acid was added for pretreatment at 120°C for 30 min. Subsequently, the samples were removed, and 1 mL of nitric acid and 1 mL of hydrogen peroxide were added in a microwave oven. The temperature and time gradient were set to 150°C and heated for 10 min, then set to 180°C. After heating for 5 min, the temperature was maintained at 200°C and heated for 30 min. After the microwave cycle was completed, the mixture was acidified to approximately 2 - 3 mL at 170°C using an acidifier, then cooled, and the volume was adjusted. The iron content was determined by ICP-MS.

[0039] Determination of iron element by MC-ICP-MS. Dry dust, control group lungs, and lungs of the 25 mg / kg dust-exposed group were placed in a digestion cell, and 9 mL of nitric acid was added. Pretreatment was carried out at 120 °C for 30 min. Subsequently, the samples were removed, and 1 mL of nitric acid and 1 mL of hydrogen peroxide were added in a microwave oven. The temperature and time gradient were set to 150 °C and heated for 10 min, then set to 180 °C. After heating for 5 min, the temperature was maintained at 200 °C and heated for 30 min. After the microwave cycle was completed, the mixture was acidified to approximately 2 - 3 mL in an acidifier at 170 °C, then cooled and the volume was adjusted. Metal stable isotope analysis of iron was performed using a multi-receiver inductively coupled plasma mass spectrometer (MC-ICP-MS) instrument and measured in high-resolution mode. Relative to the reference material IRMM-014, the isotope ratio (δ 56 Fe value) was calculated as follows: δ 56 Fe = [( 56 Fe / 54 Fe)sample / ( 56 Fe / 54 Fe)Standard]×10 3 Specifically, by comparing the proximity of the δ 56 Fe isotope ratios between the biological samples of the control group and the exposed group and the particulate matter, it was determined whether the iron element in the biological samples originated from the particulate matter. The higher the proximity, the stronger the homology.

[0040] Stable isotope fingerprints of iron in mouse dust and lungs. Indoor dust contains high levels of iron, which can enter the bloodstream through the lungs and reach the bone marrow. Transmission electron microscopy of the lungs showed the deposition of particulate matter, confirming the penetrability of the dust ( Figure 5 A). Iron staining of lung and bone marrow tissues showed obvious iron deposition, indicating iron overload ( Figure 5 B). ICP-MS analysis further showed that compared with the control group, the iron content in the lung tissue of the dust-exposed group increased by 49.99% ( Figure 5 C, p <0.05), which provided additional support for the view that iron in the dust can enter the human body. However, these results do not clearly conclude that the excessive iron observed in mice originated from the dust.

[0041] Different substances have unique isotope fingerprints or ratios, which helps to trace their environmental sources. Organisms generally have lighter iron isotopes than natural substances containing more heavy iron isotopes. Iron stable isotope ratios can be used for source determination. Therefore, to confirm that the iron in the body is derived from dust, we conducted stable isotope tests on dust and lung tissue. The isotope plot of δ57Fe vs. δ56Fe shows a linear relationship with a slope of 1.4877, indicating no mass-independent fractionation ( Figure 5 D). In addition, the δ56Fe isotope ratio is closely related to the dust exposure group and the dust itself (dust is 0.12, control group lung is −1.97, dust exposure group lung is −1.48) ( Figure 5 E, p <0.05), and the δ56Fe in the dust exposure group is closer to the dust than the control group.

[0042] These results indicate that the excess iron in the body does indeed come from dust. The iron isotopes in dust are very similar to those of igneous rocks from natural sources (0 ± 0.05), strengthening the view that the iron in dust mainly comes from natural sources. Therefore, this evidence supports the conclusion that iron from indoor dust, mainly from natural sources, can enter the bloodstream through the lungs of mice, potentially affecting bone marrow hematopoiesis and causing anemia.

[0043] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for identifying and tracing toxic metal components in indoor dust, characterized in that: By identifying the iron isotope ratios in lung tissue and dust to confirm their homology, and by comparing the proximity of the isotope ratios between biological samples and particulate matter in the control group and the exposed group, it is determined whether the iron element accumulated in the biological samples is exogenous iron introduced by indoor dust exposure.

2. The method for identifying and tracing toxic metal components in indoor dust according to claim 1, wherein: It includes the following steps: (1) Construct a health endpoint model with anemia as the effect endpoint; (2) Omics-driven mechanism analysis: Based on transcriptome sequencing of the hematopoietic organ bone marrow, the toxic metal component - iron element is screened out; (3) Verification of iron metabolism disorder: Use enzyme-linked immunosorbent assay technology and histochemical staining method to verify iron metabolism-related proteins to verify iron metabolism disorder; (4) Trace the source of iron element by combining multiple technologies: Use transmission electron microscopy TEM to observe the deposition of dust particles in lung tissue, use inductively coupled plasma mass spectrometry ICP-MS to quantify iron accumulation, and finally use multi-collector inductively coupled plasma mass spectrometry MC-ICP-MS technology to examine the iron isotope ratios in lung tissue and dust to confirm their homology, thereby determining whether the iron element accumulated in the body is exogenous iron introduced after indoor dust exposure.

3. The method for identifying and tracing the toxic metal components in indoor dust according to claim 2, characterized in that: In the tracing stage, first use transmission electron microscopy to determine the deposition of particulate matter, then use chemical means ICP-MS technology to quantify the increase of iron in tissues, and finally use MC-ICP-MS technology to detect the iron isotope ratios in tissue biological samples and particulate matter, and compare the proximity of the isotope ratios to perform source determination on the iron element, and it is found that the iron element accumulated in the exposed group comes from particulate matter outside the body.

4. The method for identifying and tracing the toxic metal components in indoor dust according to claim 1, characterized in that: Step 1): Construction of a health endpoint model: Establish a mouse model of indoor dust exposure, and confirm the anemia phenotype through routine blood test to detect hemoglobin, red blood cell count and bone marrow pathology analysis; Step 2): Omics-driven mechanism analysis: Perform transcriptome sequencing on bone marrow tissue, screen differentially expressed genes DEGs, and lock the ferroptosis pathway Ferroptosis and iron ion binding-related biological processes through KEGG / GO enrichment analysis; Step 3): Verification of iron metabolism disorder: Use ELISA to quantify serum hepcidin Hepcidin, ferritin FE, and transferrin receptor TFRC in lung and bone marrow tissues, and combine Prussian blue staining to localize iron deposition in lung and bone marrow organs; Step 4): Trace the source of iron element by combining multiple technologies: TEM electron microscopy: Observe the ultrastructure of the lung to determine the deposition of particulate matter; ICP-MS: Detect the iron content in lung tissue and quantify the accumulation of iron element; MC-ICP-MS: Determination of δ 56 Fe isotope ratio to determine the homology of lung iron and dust iron.

5. The method for identifying and tracing toxic metal components in indoor dust according to claim 4, wherein: In step 4, TEM is used to examine the deposition of particulate matter. Specifically: collect lung tissues of mice smaller than 2 mm 3 and preserve them in 2.5% glutaraldehyde; after at least 24 hours, dehydrate the samples and then fix them with 1% osmium tetroxide solution; after dehydration with ethanol, embed the specimens in epoxy resin, cut into ultrathin sections, and then stain with 2% uranyl acetate and 3% lead citrate; use a transmission electron microscope to detect the ultrastructure of the mouse lungs and observe whether there is particulate matter deposition in the lung tissues.

6. The method for identifying and tracing toxic metal components in indoor dust according to claim 4, wherein: In step 4, the iron element was detected by ICP-MS. Specifically, the dry dust, the control group lungs, and the 25 mg / kg body weight dust exposure group were placed in a digestion cell, 9 mL of nitric acid was added, and pretreatment was carried out at 120 °C for 30 min; subsequently, the samples were removed, 1 mL of nitric acid and 1 mL of hydrogen peroxide were added in a microwave oven; the temperature and time gradient were set to heat at 150 °C for 10 min, heat at 180 °C for 5 min, and then maintain the temperature at 200 °C for 30 min; after the microwave cycle was completed, the acidifier acidified the mixture to 2-3 mL at 170 °C, then cooled, and the volume was adjusted; the iron content was determined by an inductively coupled plasma-mass spectrometer (ICP-MS) instrument.

7. The method for identifying and tracing toxic metal components in indoor dust according to claim 4, wherein: In step 4, iron element was detected by MC-ICP-MS, specifically as follows: dry dust, the lungs of the control group, and the dust exposure group at 25 mg / kg body weight were placed in a digestion cell, 9 mL of nitric acid was added, and pretreatment was carried out at 120 °C for 30 min. Subsequently, the sample was removed, 1 mL of nitric acid and 1 mL of hydrogen peroxide were added in a microwave oven, and the temperature and time gradient were set to heat at 150 °C for 10 min, heat at 180 °C for 5 min, and then maintain the temperature at 200 °C for 30 min. After the microwave cycle was completed, the mixture was acidified to 2-3 mL at 170 °C using an acidifier, then cooled and the volume was adjusted. The metal stable isotope analysis of iron was carried out using a multi-receiver inductively coupled plasma mass spectrometer (MC-ICP-MS) instrument, and the measurement was carried out in high-resolution mode. Relative to the reference material IRMM-014, the isotope ratio (δ 56 Fe value) was calculated: δ 56 Fe = ([( 56 Fe / 54 Fe) sample / ([( 56 Fe / 54 Fe) standard] × 10 3 ; Compare the proximity of the δ 56 Fe isotope ratio between the biological samples and particulate matter in the control group and the exposed group to determine whether the iron in the biological samples comes from particulate matter. The higher the proximity, the stronger the homology.

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