Application of hydrogen-rich water in improvement of chronic aluminum exposure mouse injury

Abstract

The invention discloses an application of hydrogen-rich water in improving chronic aluminum exposure mouse injury. The injury caused by chronic aluminum exposure comprises at least one of nerve injury, liver and kidney injury, intestinal barrier injury and blood brain barrier injury. The product is a beverage, a health care product or a medicine. The improvement effect is realized by adjusting a microorganism-intestinal-brain axis, including up-regulating the abundance of beneficial bacteria in the intestinal tract; the level of anti-inflammatory metabolites baicalein and indole-3-ethanol is increased, and the expression of inflammatory factors interleukin 6, interleukin 1 beta and tumor necrosis factor a is reduced; inflammation and oxidative stress reaction caused by chronic aluminum exposure can be remarkably relieved through hydrogen-rich water intervention, and meanwhile the liver and kidney functions can be effectively improved. In addition, abnormal behaviors of chronic aluminum exposure mice are improved, and the level of beta-amyloid protein in brains of the mice is remarkably reduced; the hydrogen-rich water is prompted to improve the abundance of beneficial bacteria, so that the bacteria have a protection effect on the organism with chronic aluminum exposure through the effects of resisting oxidation, resisting inflammation, protecting nerves and the like.

Description

TECHNICAL FIELD

[0001] The embodiment of the present application relates to the technical field of biological medicine, and particularly relates to application of hydrogen-rich water in improving damage of chronic aluminum exposure mice. BACKGROUND

[0002] Aluminum is the most abundant metal element in the earth's crust, and has a wide range of applications in our lives. In recent years, with the development of manufacturing industry, and the application of aluminum-containing cosmetics and food additives in life, the damage caused by aluminum exposure to the human body has attracted more and more attention. Aluminum ions in the human body not only have no function, but also cause certain damage to the human body, so that excessive exposure to aluminum will have an indelible impact on the body, and the aluminum ingested through the digestive tract is particularly worth paying attention to. As a common element in nature, aluminum is contained in almost all food or drinking water, and monitoring and focusing on the aluminum content ingested in the diet of residents is a key problem. After aluminum ions enter the human body through diet, they are absorbed through the stomach and small intestine, and widely distributed in the human body through the circulatory system. The aluminum ions absorbed into the human body will cause damage to multiple organs and tissues including bones, liver, kidneys, brain, intestines, etc. through inflammatory response and oxidative stress response. In addition, aluminum absorbed through the intestinal tract will not only cause oxidative stress and inflammatory response in the intestinal tract, but also damage the intestinal barrier, leading to increased intestinal permeability, further enhancing the absorption of aluminum. According to the research results in recent years, the excessive aluminum ions in the human body are directly related to neurodegenerative diseases such as Alzheimer's disease, which may play a certain role in oxidative stress, mitochondrial dysfunction, iron and calcium homeostasis disorders, neuroinflammation, and aggregation of beta-amyloid protein. Therefore, intervention in chronic aluminum poisoning through certain means has important significance for reducing damage to the nervous system and other organs and tissues, improving the prognosis of patients, and preventing potential health risks, and helps to protect human health. Metal chelators such as Deferiprone (DFP) are traditional drug means to intervene in aluminum ion exposure and aluminum poisoning, but the use of these chelators may have certain side effects on the body, such as agranulocytosis, abnormal liver function, etc., so it is not an ideal intervention means. Therefore, finding a more convenient and safe way to intervene in chronic aluminum poisoning has become a goal.

[0003] The role of hydrogen molecules in the field of health has been a hot topic in recent years. Many studies have shown that hydrogen molecules have a wide range of therapeutic potential in sepsis, malignant tumors, Alzheimer's disease and other diseases and health problems through their antioxidant, anti-inflammatory, immune regulation, metabolic improvement and neuroprotection mechanisms. Hydrogen-rich water (HRW) as a portable, safe and easy to consume intake method has received more and more attention in recent years. Many studies have shown that hydrogen-rich water has anti-inflammatory, antioxidant and intervention effects on neurodegenerative diseases and colitis. Due to the positive role of hydrogen-rich water in the intervention of these diseases, it is speculated that it can improve the damage caused by chronic aluminum exposure. The microbiota-gut-brain axis is a two-way communication between the gut microbiota and the central nervous system. The microbiota-gut-brain axis can affect the progression of neurodegenerative diseases in many ways by regulating neural inflammation, neurotransmitter levels, intestinal barrier and blood-brain barrier integrity, vagus nerve and autonomic nervous system signaling, and metabolite production, providing new potential targets for the treatment of related diseases. Therefore, the present application constructs a mouse model of chronic aluminum exposure to explore the intervention effect of hydrogen-rich water on chronic aluminum exposure and its mechanism of action, focusing on its regulatory effect on the intestinal barrier, blood-brain barrier and microbiota-gut-brain axis. SUMMARY

[0004] The present application aims to provide the application of hydrogen-rich water in improving the damage of chronic aluminum exposure mice. The present application constructs a mouse model of chronic aluminum exposure, conducts behavioral tests, detects related biochemical indicators such as oxidation and inflammation, evaluates the integrity of the intestinal barrier and blood-brain barrier, and detects the level of brain beta amyloid, to further explore the intervention effect of hydrogen-rich water on chronic aluminum exposure mice. The study also uses metagenomic and non-targeted metabolomic research to further explore the possible mechanism of action of hydrogen-rich water on chronic aluminum exposure mice through the microbiota-gut-brain axis.

[0005] Specifically, it includes the following steps:

[0006] 1. Constructing an animal model and intervening it: 36 C57 mice are divided into a CON group (control group), an AL group (aluminum exposure group), an HRW group (hydrogen-rich water intervention group) and a DFP group (deferiprone intervention group). The AL, HRW and DFP groups freely drink water containing aluminum (200 mg / L) for the first 8 weeks, and then recover ordinary drinking water for the last 6 weeks; the HRW group is given hydrogen-rich water (0.2 mL, hydrogen concentration 1.6 ppm) by gavage every day throughout the process, and the DFP group is given DFP solution (2.5 g / L) by gavage.

[0007] 2. Behavioral assessment: Y maze (spatial memory), novel object recognition (recognition memory) and open field test (anxiety behavior) are performed from the 12th to the 14th week.

[0008] 3. Related index detection: ELISA method is used to detect serum proinflammatory factors (interleukin 1 beta, interleukin 6, tumor necrosis factor a); serum antioxidant indexes (glutathione, superoxide dismutase) and liver and kidney injury markers (glutamic-pyruvic transaminase, glutamic oxalacetic transaminase, urea nitrogen) are detected; liver tissue pathology is evaluated by HE staining; ELISA method is used to detect brain beta-amyloid (beta-amyloid 1-40, beta-amyloid 1-42); intestinal permeability indicators (D-lactic acid, diamine oxidase) and barrier protein (ZO-1, Occludin) expression levels are detected.

[0009] 4. Multi-omics analysis: metagenomic sequencing is used to analyze intestinal flora structure, non-targeted metabolomics is used to detect fecal metabolites, and correlation analysis is used to reveal microbe-intestine-brain axis mechanism.

[0010] The present application finds that:

[0011] (1) Hydrogen-rich water can significantly affect anxiety behavior and memory learning impairment caused by chronic aluminum exposure: hydrogen-rich water significantly reverses the decrease in spontaneous alternation times (Y maze), the shortening of new object exploration time and anxiety behavior (open field test) caused by aluminum exposure (P<0.05);

[0012] (2) Hydrogen-rich water has anti-inflammatory and antioxidant effects: the levels of proinflammatory factors (interleukin 1 beta, interleukin 6 and tumor necrosis factor a) are significantly increased in the aluminum exposure group, and the antioxidant indexes (glutathione, superoxide dismutase) are decreased; after hydrogen-rich water intervention, the above indexes are significantly restored, and the effects of reducing interleukin 6 and increasing superoxide dismutase are better than those of DFP (P<0.05);

[0013] (3) Hydrogen-rich water has organ protection effect: hydrogen-rich water significantly reduces the levels of glutamic-pyruvic transaminase, glutamic oxalacetic transaminase and urea nitrogen in aluminum exposure mice (P<0.05), improves liver tissue inflammatory infiltration and structural damage; at the same time, it reduces the deposition of brain beta-amyloid 1-40 and beta-amyloid 1-42 (P<0.05), indicating that it has neuroprotective effect.

[0014] (4) Hydrogen-rich water has barrier function repair effect: hydrogen-rich water up-regulates the expression of intestinal and brain tissue tight junction proteins (ZO-1, Occludin), and reduces the levels of serum D-lactic acid and diamine oxidase (P<0.05), thereby repairing the integrity of intestinal barrier and blood-brain barrier.

[0015] (5) Microbiota and metabolite regulation: metagenomics showed that the composition of the HRW group was close to the CON group, and the abundance of Bacteroides in the AL group was significantly reduced, and the abundance of Roseburia and other beneficial bacteria was significantly increased after HRW intervention (P<0.05). Metabolomics found that HRW up-regulated anti-inflammatory metabolites such as baicalein and indole-3-ethanol, and down-regulated oxidative stress markers such as 3-nitrotyrosine. Correlation analysis showed that Bacteroides was negatively correlated with beta-amyloid levels, and Roseburia was negatively correlated with inflammatory factor levels, and key metabolites were significantly associated with the abundance of probiotics.

[0016] Based on the above, the technical scheme provided by the present application is:

[0017] The application of hydrogen-rich water in improving the damage of chronic aluminum exposure mice, wherein the damage caused by chronic aluminum exposure includes at least one of nerve damage, liver and kidney damage, intestinal barrier damage and blood-brain barrier damage.

[0018] Preferably, the product is a drink, a health product or a medicine.

[0019] Preferably, the improvement is achieved by regulating the microbiota-gut-brain axis, including up-regulating the abundance of intestinal beneficial bacteria Roseburia and Bacteroides, and down-regulating the oxidative metabolite 3-nitrotyrosine.

[0020] Preferably, the regulation includes increasing the levels of anti-inflammatory metabolites baicalein and indole-3-ethanol, and reducing the expression of inflammatory factors interleukin 1β, interleukin 6 and tumor necrosis factor a.

[0021] The application also discloses a pharmaceutical composition for improving the damage of chronic aluminum exposure mice, which contains hydrogen-rich water as an active ingredient and a pharmaceutically acceptable carrier.

[0022] Chronic aluminum exposure may mainly affect healthy organisms by reducing certain metabolites with anti-inflammatory, antioxidant or neuroprotective effects. After HRW intervention, some metabolites that play a protective role in intestinal mucosal barrier and anti-inflammatory effect increase, and some disease markers decrease, which further proves that the health status of aluminum exposure mice shows an improvement trend after HRW intervention. The results of correlation analysis also suggest that the above metabolites such as N-acetylneuraminic acid, soy sterol B and indole-3-ethanol are positively correlated with most of the probiotics in the intestine; at the same time, 3-nitrotyrosine and 3-oxo-octadecanoic acid ethyl ester as a marker of organism damage are negatively correlated with the above-mentioned beneficial bacteria.

[0023] Overall, hydrogen-rich water intervention can significantly alleviate inflammation and oxidative stress induced by chronic aluminum exposure, and can effectively improve liver and kidney function; hydrogen-rich water intervention improves the abnormal behavior of mice exposed to chronic aluminum and significantly reduces the level of beta-amyloid in the brain; it is suggested that hydrogen-rich water can improve the abundance of beneficial bacteria, and these bacteria can protect the body from chronic aluminum exposure through antioxidant, anti-inflammatory, and neuroprotective effects; hydrogen-rich water may regulate the intestinal barrier, blood-brain barrier, intestinal flora and its metabolite levels, and play a protective role through the microbiota-gut-brain axis. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 Results of the mouse behavior experiment.

[0025] (A) Y maze experiment results of mice; (B) new object recognition experiment results of mice; (C) open field experiment results of mice; (*: P<0.05, **: P<0.01, ***: P<0.001, ****: P<0.0001, ns no statistical significance);

[0026] Figure 2 Serum pro-inflammatory factor levels of mice;

[0027] (A) interleukin 1β levels; (B) interleukin 6 levels; (C) tumor necrosis factor a levels;

[0028] (*: P<0.05, **: P<0.01, ***: P<0.001, ****: P<0.0001, ns no statistical significance);

[0029] Figure 3 Oxidative stress indicators in the serum of mice;

[0030] (A) glutathione levels; (B) superoxide dismutase levels;

[0031] (*: P<0.05, **: P<0.01, ***: P<0.001, ****: P<0.0001, ns no statistical significance);

[0032] Figure 4 Liver and kidney injury indicators in mice;

[0033] (A) alanine aminotransferase levels; (B) aspartate aminotransferase levels; (C) urea nitrogen levels;

[0034] (*: P<0.05, **: P<0.01, ***: P<0.001, ****: P<0.0001, ns no statistical significance);

[0035] Figure 5HE staining of liver tissue of mice

[0036] Figure 6 β-amyloid levels in brain tissue of mice

[0037] (A) β-amyloid 1-40 levels; (B) β-amyloid 1-42 levels

[0038] (*: P < 0.05, **: P < 0.01, ***: P < 0.001, ns not statistically significant)

[0039] Figure 7 Expression of tight junction proteins Occludin and ZO-1 in the brain of mice at the gene and protein levels

[0040] (A) qPCR detection of gene expression; (B) Western Blot detection of protein expression

[0041] (*: P < 0.05, **: P < 0.01, ***: P < 0.001, ns not statistically significant)

[0042] Figure 8 Intestinal permeability index of mice

[0043] (A) D-lactic acid levels; (B) diamine oxidase levels

[0044] (*: P < 0.05, **: P < 0.01, ***: P < 0.001, ns not statistically significant)

[0045] Figure 9 Expression of tight junction proteins Occludin and ZO-1 in the intestine of mice at the gene and protein levels

[0046] (A) qPCR detection of gene expression; (B) Western Blot detection of protein expression

[0047] (*: P < 0.05, **: P < 0.01, ***: P < 0.001, ****: P < 0.0001, ns not statistically significant)

[0048] Figure 10 Beta diversity analysis of intestinal flora

[0049] (A) Principal component analysis; (B) Principal coordinate analysis

[0050] Figure 11 Species composition analysis of intestinal flora

[0051] (A) the relative abundance of species at genus level; (B) the relative abundance of species at species level;

[0052] Figure 12 Differential analysis of species of gut microbiota;

[0053] (A) the distribution of LDA values of differential species; (B) the difference in abundance of colonies between the CON group and the AL group; (C) the difference in abundance of colonies between the AL group and the HRW group; (*: P < 0.05, **: P < 0.01)

[0054] Figure 13 Principal component analysis and orthogonal partial least squares discriminant analysis of groups;

[0055] (A-B) three-dimensional results of principal component analysis; (C-D) score plots of orthogonal partial least squares discriminant analysis.

[0056] Figure 14 Differential metabolite analysis between different groups;

[0057] (A) the Venn diagram of differential metabolites; (B) differential metabolites common to the three groups; (C) a heat map of differential metabolites between the AL group and the CON group; (D) a heat map of differential metabolites between the HRW group and the AL group;

[0058] Figure 15 Correlation analysis of differential microbiota and biochemical indicators; (*: P < 0.05, **: P < 0.01, ***: P < 0.001)

[0059] Figure 16 Multi-omics correlation analysis;

[0060] (A) correlation analysis of differential metabolites and differential microbiota between the AL group and the CON group; (B) correlation analysis of differential metabolites and differential microbiota between the HRW group and the AL group; (*: P < 0.05, **: P < 0.01, ***: P < 0.001). DETAILED DESCRIPTION

[0061] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations.

[0062] Embodiment:

[0063] First, the basic situation of some biological materials and experimental equipment involved in the following embodiments is briefly described as follows.

[0064] Biological material:

[0065] Experimental animals: 36 male C57BL / 6 mice (6 weeks old, body weight range 20-25 g) were selected for this study, provided by Beijing Vantoll Life Experimental Animal Technology Co., Ltd. (Experimental Animal Production License No. SCXK (Zhejiang) 2019-0001). The experimental animals were raised in the SPF barrier facility of the Experimental Animal Center of Zhengzhou University, with environmental parameters strictly controlled at a temperature of 20-22°C, a relative humidity of 50%-60%, and a 12-hour light / dark cycle. All experimental subjects had free access to standard feed and sterile drinking water. The research program was approved by the Ethics Committee of the Fifth Affiliated Hospital of Zhengzhou University (Approval Number: KY2023144).

[0066] Table 1 Experimental reagents:

[0067]

[0068]

[0069]

[0070] Example 1

[0071] This example explores the intervention effect of hydrogen-rich water on chronic aluminum exposure and its mechanism by constructing a mouse model of chronic aluminum exposure. The relevant experimental process is briefly introduced as follows:

[0072] 1. Animal grouping and treatment

[0073] The 36 adult male C57BL6 mice were randomly divided into the CON group (control group), the AL group (aluminum exposure group), the HRW group (hydrogen-rich water intervention group), and the DFP group (deferiprone intervention group).

[0074] AlCl3·6H2O was dissolved in drinking water to prepare a solution with an aluminum ion concentration of 200 mg / L for free drinking; DFP was prepared as a 2.5 g / L solution for gavage.

[0075] The experimental scheme is shown in Table 2. The AL group, the HRW group and the DFP group were allowed to freely drink the drinking water containing aluminum ions at a concentration of 200 mg / L for the first 8 weeks, and were respectively given 0.2 mL of ordinary water, hydrogen-rich water (0.8 mmol / L) and DFP solution (2.5 g / L) by gavage every day. From the 9th week to the 14th week, the three groups continued to be given by gavage, and the drinking water containing aluminum ions was changed to ordinary drinking water. The CON group drank ordinary water and was given ordinary water by gavage throughout the experiment. The hydrogen-rich water was prepared using a hydrogen-rich water cup. The hydrogen-rich water prepared by the hydrogen-rich water cup has been measured by gas chromatograph for many times (the average concentration is 1.6 ppm), and is prepared on site during the experiment. A portable hydrogen-rich water detection pen is used to detect the hydrogen concentration of the hydrogen water to ensure that the average hydrogen concentration is 0.8 mmol / L (1.6 ppm).

[0076] The experiment was carried out to the 12th week, the 13th week and the 14th week, and three kinds of behavior experiments were carried out. After the 14th week experiment was completed, the mice were sacrificed, and the blood samples, liver, small intestine and brain tissues of the mice were obtained, and the cecum contents were collected.

[0077] Table 2 Experimental design scheme of chronic aluminum exposure mice

[0078]

[0079] Note: No aluminum water: ordinary drinking water for free drinking. Aluminum water: free drinking of a solution containing aluminum ions at a concentration of 200 mg / L. Hydrogen-rich water: 0.2 mL of hydrogen-rich water with a concentration of about 0.8 mmol / L is given by gavage every day. DFP: 0.2 mL of DFP solution at 2.5 g / L is given by gavage every day. Ordinary water: 0.2 mL of ordinary drinking water is given by gavage every day.

[0080] 2. Behavior experiment of mice

[0081] (1) Y maze

[0082] The Y maze spontaneous alternation test was carried out at the 12th week. The experiment was carried out in a symmetrical black resin glass Y maze, which had three arms (20 cm long x 10 cm wide x 20 cm high) at a right angle of 120°, designated as A, B and C. The mice were placed at the distal end of the A arm and allowed to explore the maze for 8 minutes. The movement trajectory of the mice was recorded using a camera installed above the maze. In order to avoid the influence of the smell of the mice on each other, the space in the box was wiped with 75% ethanol after each mouse test. The arms entered by the mice were recorded, and the following formula was used to calculate: alternation percentage (one alternation for continuously entering three different arms) = alternation times / (total number of arm entries - 2).

[0083] (2) Novel object recognition experiment

[0084] The new object recognition experiment was performed at week 13. The new object recognition experiment was performed in an open field (25 cm x 25 cm). A video camera mounted above the open field recorded the movement of the mice during the entire experiment. The first day, the mice were first given a 5-minute habituation trial with no objects in the open field. This was followed by a test phase consisting of two trials, 24 hours apart. In the first trial, two identical objects were placed in opposite regions of the field and the mice were allowed to explore them for 5 minutes. In the second trial, 15 minutes later, one of the objects was replaced with a new object and the mice were again placed in the maze for a second 5-minute exploration trial. During behavioral observation, the experimental animals were defined as valid exploration behavior if they exhibited nose contact or head orientation towards the target object (distance ≤ 1 cm). The cumulative exploration time of the two target objects by the subjects was recorded using a video analysis system. In addition, to eliminate the interference of odor, after each round of testing was completed, the inner wall and contact surface of the experimental device were standardized cleaned using 75% ethanol. The items used were small plastic toys of similar size. Finally, Smart3.0 tracking software was used for analysis. Recognition index (DI) = new object exploration time / (new object exploration time + old object exploration time)

[0085] (3) Open field experiment

[0086] The open field experiment was performed at week 14. The mice were placed in a 25 cm x 25 cm black resin glass box with their faces against the wall and allowed to explore for 10 minutes. The session was recorded using an overhead video camera, and the Smart3.0 tracking software was used to analyze the number of times the mice entered the central area, the time spent in the central area, and the proportion of the distance walked in the central area.

[0087] 3. Detection of inflammation and oxidation indicators

[0088] The levels of interleukin 6, interleukin 1β, and tumor necrosis factor a in the serum of mice were detected by ELISA, and the corresponding kits were purchased from Vanke Wei Biological Company. The specific operation was carried out according to the kit instructions.

[0089] The level of glutathione in the serum of mice was detected by microplate method, and the level of superoxide dismutase in the serum was detected by WST-1 method. The above kits were purchased from Nanjing Jiancheng Biological Company, and the operation steps were strictly performed according to the instructions.

[0090] 4. Tissue damage indicators

[0091] The levels of glutathione and glutathione in the serum of mice were detected by microplate method, and the level of urea nitrogen in the serum of mice was detected by urease method. The above kits were purchased from Nanjing Jiancheng Biological Company, and the operation was carried out strictly according to the instructions.

[0092] 5. HE staining of tissues

[0093] (1) Tissue fixation, dehydration, embedding and sectioning

[0094] Fixation: Mouse liver tissues were fixed in 4% paraformaldehyde solution for 24 hours.

[0095] Dehydration: After loading the liver tissue samples into a special embedding box, they were sequentially immersed in gradient ethanol solutions for pretreatment (50% ethanol for 30 minutes, 60% ethanol for 30 minutes). After completing the gradient dehydration pretreatment, the samples were transferred to a specimen basket compatible with the automatic dehydration machine and the standardized dehydration process was performed according to the preset program: gradient ethanol dehydration program (70%, 80%, 90%, 95% ethanol for 1 hour each, with 95% ethanol repeated twice), followed by two dehydration treatments with anhydrous ethanol (1 hour each). Subsequently, the samples were sequentially treated with xylene-ethanol mixture (1:1 by volume) for 30 minutes, twice with xylene for 15 minutes each, and finally embedded with 60°C liquid paraffin for 1 hour each.

[0096] Paraffin embedding: The embedding machine was preheated to 62°C, and the cold table was set to -20°C. Using a metal mold, the tissue was placed with the largest section facing down, and after pouring the molten paraffin, it was quickly transferred to the cold table for solidification to avoid paraffin crystallization.

[0097] Tissue sectioning, flattening, fishing, and baking: The paraffin-embedded tissue was equilibrated in an ice water bath for 2 hours to enhance section stability. The slide flattening instrument (45°C) and slide baking instrument (60°C) were preheated. The sample was fixed on the stage of the microtome, and after rough trimming to 10 pm thickness to smooth the section, it was adjusted to 4 pm thickness for continuous sectioning. The morphologically intact sections were selected and placed in the flattening instrument, and after the tissue was completely stretched, the sections were quickly captured using the inclined immersion method with a glass slide to ensure no air bubbles remained. After draining, it was transferred to the baking instrument for 60°C constant temperature solidification for 60 minutes, and the finished sections were stored at room temperature in a sealed container.

[0098] (2) HE staining

[0099] Tissue deparaffinization and rehydration: 60°C pre-baking for 30 minutes to accelerate paraffin dissolution, gradient deparaffinization program: xylene I, II for 9 minutes each, anhydrous ethanol I, II for 2 minutes each, 95% ethanol I, II for 2 minutes each, 80% ethanol for 1 minute, 75% ethanol for 1 minute, and finally rinsed with tap water for 2 minutes to remove residual reagents.

[0100] Nuclear staining: Hematoxylin immersion staining for 3 minutes (optimized based on pre-experiment results) and rinsing with running water for 1 minute until the cell nuclei appeared light blue.

[0101] Differentiation and cytoplasmic staining: After placing the sections in the differentiation solution for 2-5 seconds, they were quickly rinsed with running tap water for 15 minutes. Then the sections were placed in the eosin staining solution for 1 minute and quickly dehydrated.

[0102] Gradient dehydration and sealing: slice in 75% ethanol 15s, 85% ethanol 25s, 95% ethanol I, II each 1 min, anhydrous ethanol I, II each 2 min, xylene I, II each 2 min. Drop neutral gum, cover with cover glass, wipe off excess gum and place on a slice plate in the fume hood overnight. Observe under microscope and take pictures.

[0103] 6. β-amyloid level

[0104] The levels of β-amyloid 1-40 and β-amyloid 1-42 in mouse brain tissue were detected using mouse β-amyloid 1-40 ELISA kit and mouse β-amyloid 1-42 ELISA kit purchased from Vankyo Biotech Co., Ltd., and the specific operation was according to the kit instructions.

[0105] 7. RT-qPCR detection of mouse intestinal or brain tissue related gene expression

[0106] (1) Extraction of total RNA from mouse intestinal or brain tissue

[0107] An appropriate amount of mouse intestinal or brain tissue was cut with sterile scissors and placed in an EP tube, 600 μL of RNAiso Plus and one grinding magnetic bead were added to each tube. The tissue homogenate was prepared using the MP homogenizer with the appropriate mode, and the tissue was placed in an ice box for cooling. The homogenate was centrifuged at 4°C, 12000xg for 10 min, and the supernatant was taken.

[0108] An equal volume of chloroform was added to each tube, and the EP tube rack was inverted up and down to mix thoroughly. After standing at room temperature for 15 min, centrifugation was performed at 4°C, 12000xg for 15 min.

[0109] The liquid in the EP tube was divided into three layers after centrifugation was completed, and the supernatant was taken to a new EP tube (note that the middle layer should not be touched when taking). An equal volume of pre-cooled isopropanol was added to each tube, and the EP tube rack was inverted up and down to mix thoroughly. After standing at room temperature for 30 min, centrifugation was performed at 4°C, 12000xg for 15 min.

[0110] The precipitate was washed twice with 4°C pre-cooled 75% ethanol (sterile and enzyme-free water) (4°C, 12,000xg, 5 min). After drying at room temperature for 10 min, it was dissolved with an appropriate amount of sterile and enzyme-free water. Start the spectrophotometer and select the nucleic acid quantification module. After baseline calibration with sterile and enzyme-free water, measure the absorbance value of the RNA sample (purity standard: A260 / A280 = 1.9-2.1). According to the test results, it was labeled and quickly transferred to a pre-cooled low-temperature protection box, and finally stored in a -80°C ultra-low temperature refrigerator to maintain the stability of nucleic acids.

[0111] Reverse transcription reaction

[0112] According to different RNA concentrations, calculate the required solution volume, ensure that the mass of RNA added is 1 μg.

[0113] According to the instructions of HiScriptII 1st Strand cDNA Synthesis Kit, add 2xRTMix 10 μL, HiScriptII EnzymeMix 2 μL, Oligo(dT)23VN 1 μL, Randomhexamers 1 μL and calculated RNA solution, and use sterile enzyme-free water to make up to 20 μL.

[0114] After the sample is added, mix thoroughly, and set the reaction conditions of the PCR instrument as follows: 25℃ for 5 min, 50℃ for 15 min, and 85℃ for 2 min.

[0115] (3) Design primers

[0116] Obtain the primer sequence through PrimerBank, verify the specificity through NCBI Primer-BLAST, and then synthesize the sequence through Shengong Biotechnology (HPLC purification). The primer sequence is shown in Table 3:

[0117] Table 3 Primer sequence

[0118]

[0119] (4) Real-time fluorescent quantitative PCR reaction

[0120] Mix, primers, cDNA and sterile enzyme-free water are mixed in proportion (final volume 20 μL), gently blown and sucked by micropipette, and then transferred to ice for temporary storage. The mixture is sequentially dispensed into the corresponding hole sites of the eight-pipe reaction plate, vortexed, mixed and degassed, and then placed in the real-time fluorescent quantitative PCR instrument for reaction. The program is: 95℃ for 30 sec; 95℃ for 5 sec, 60℃ for 30 sec, 40 cycles; melting curve analysis (60℃→95℃, 0.5℃ / s). After the reaction, β-actin is used as the internal reference, and the 2-△△Ct method is used for calculation.

[0121] 8. Western Blot detection of mouse intestinal or brain tissue related protein expression

[0122] (1) Sample preparation and protein extraction

[0123] Take 30 mg of tissue sample, add pre-cooled RIPA lysis buffer (containing 1% protease inhibitor and 1% phosphatase inhibitor), and use ultrasonic disrupter for tissue disruption. Centrifuge the lysis buffer at 4°C, 12000 x g for 15 min, and collect the supernatant. Then use the BCA method to determine the protein concentration, adjust to a uniform concentration, add 5x Loading buffer, boil at 95°C for 5 min, and store at -80°C after aliquoting.

[0124] (2) SDS-PAGE electrophoresis

[0125] Prepare the SDS-PAGE gel according to the kit instructions, and add an appropriate amount of marker on one side according to the design, and add the same amount of sample to the rest of the holes (vertical oblique 45° when loading). After loading, place the electrophoresis clamp in the electrophoresis tank, add an appropriate amount of electrophoresis liquid, align the positive and negative electrodes, turn on the power, adjust the voltage to 80V, and when the sample strip just runs into the lower layer of glue, adjust the voltage to 120V. Turn off the power when the sample strip runs to about 0.5 cm from the lower edge of the gel plate.

[0126] (3) Transmembrane

[0127] After electrophoresis, cut the gel in the target protein range and place it in the transmembrane liquid. Soak the membrane and transmembrane clamp in the transmembrane liquid, and complete the placement in the order of blackboard, pad, filter paper, gel, membrane, filter paper, pad, whiteboard. Clamp the transmembrane clamp and place it in the transmembrane tank (note the positive and negative), and add an appropriate amount of transmembrane liquid. Constant current 250mA transmembrane 90min (adjust the time according to the molecular weight of the protein).

[0128] (4) Blocking and antibody incubation

[0129] After transmembrane, place the membrane in 5% skim milk (TBST preparation) and shake at room temperature for 1h. Dilute the primary antibody with BSA-TBST (ratio according to the antibody instructions), and incubate the membrane with the primary antibody at 4°C overnight (12-16h). After incubation with the primary antibody, wash with TBST 3 times x 10 min. Dilute the secondary antibody according to the instructions, and incubate the membrane with the secondary antibody at room temperature for 1h, and wash with TBST 3 times x 10 min.

[0130] (5) Chemiluminescence detection

[0131] Mix ECL luminescent liquid A / B at a ratio of 1:1, evenly cover the surface of the membrane, and incubate in the dark for 1 min. Use ChemiDocMP imaging system to collect the signal, and adjust the exposure time to avoid saturation. Finally, quantitative analysis: ImageLab6.1 software calculates the gray ratio of the target protein and the internal reference.

[0132] 9. Intestinal permeability index determination

[0133] Diamine oxidase levels in serum were detected using a mouse diamine oxidase ELISA kit purchased from Vanco Biotech, and D-lactic acid levels in serum were detected using a D-lactic acid colorimetric kit purchased from Elabscience. The above kits were operated according to the instructions.

[0134] 10. Metagenomic analysis

[0135] (1) DNA extraction

[0136] After collecting the mouse fecal samples, they were immediately stored at -80°C. Genomic DNA was extracted using the DNeasy PowerSoil Pro Kit (Qiagen), and the specific operation was performed according to the instructions. The DNA concentration (A260 / A280 ratio should be between 1.8 and 2.0) was measured using a NanoDrop 2000 spectrophotometer, and the DNA integrity was verified by 1% agarose gel electrophoresis. 1 ng of high-quality DNA was taken from each sample for subsequent library construction.

[0137] (2) Library construction and sequencing

[0138] Library preparation was performed using the Vazyme TruePrep DNA Library Prep Kit: After the genomic DNA was detected to be qualified, it was broken to a target fragment length of 350 bp using an ultrasonic disrupter, then end repair, A tailing and ligation of sequencing adapters were performed, followed by PCR amplification. The PCR product was purified by AMPure XP magnetic beads, then quantified using a Qubit 3.0 fluorometer, and the library quality was evaluated by an Agilent 2100 Bioanalyzer. The qualified library was mixed after balancing, and then subjected to double-end 150 bp sequencing on the MGIseq-2000 sequencing platform.

[0139] (3) Bioinformatics analysis

[0140] (1) The raw data was subjected to quality control using fastp: low-quality reads (Phred score < Q20) were removed; the first and last N bases were truncated; reads with a length < 50 bp were filtered; and the data after quality control was saved as clean reads.

[0141] (2) Species annotation: the protein sequence was aligned to the bacterial library of NR (downloaded version on 20210213) by diamond (v2.0.9) software, and then based on the taxonomic annotation information in the NR reference database, the microbial taxonomy annotation was performed by a phylogenetic analysis process. Subsequently, the quantitative detection data of the genes corresponding to each taxonomic unit were integrated, and the relative abundance value of a specific taxonomic group was calculated using the cumulative summation algorithm. This analysis process strictly followed the standard calculation method for quantitative metagenomic research.

[0142] (3) Statistical analysis: Principal component analysis (PCA) based on Euclidean distance, Principal coordinate analysis (PCoA) based on Bray-Curtis distance matrix. Species differences between groups: LEfSe analysis (LDAscore > 3.0, P < 0.05).

[0143] 11. Untargeted metabolomics

[0144] (1) Sample extraction

[0145] The cryopreserved mouse fecal samples were thawed on ice, and 20 mg (± 1 mg) of sample was weighed into a corresponding numbered centrifuge tube, followed by the addition of 400 μL of 70% methanol water internal standard extraction solution, and vortexed for 3 min. The sample was further sonicated for 10 min in an ice water bath, and after vortexing for 1 min twice, the sample was left to stand in a -20 °C refrigerator for 30 min to promote the dissolution of metabolites, and then centrifuged at 12000 x g for 10 min at 4 °C. 300 μL of supernatant was quantitatively transferred to a new labeled tube using a pipette. After repeating the centrifugation at 12000 x g for 3 min at 4 °C, 200 μL of clear supernatant was accurately pipetted into a special injection bottle liner for LC-MS, and immediately subjected to chromatography-mass spectrometry analysis.

[0146] (2) Chromatography-mass spectrometry analysis

[0147] After sample extraction, liquid chromatography analysis was performed using an Agilent 1290 Infinity LC UHPLC system. An AB Sciex TripleTOF 6600 mass spectrometer was used for separation using a Waters ACQUITY Premier HSS T3 chromatographic column (1.8 μm particle size, 2.1 x 100 mm size), with mobile phase A: 0.1% formic acid / water; mobile phase B: 0.1% formic acid / acetonitrile, and chromatographic parameters set as follows: column oven maintained at 40 °C constant temperature, mobile phase flow rate 0.4 mL / min, automatic injector set to 4 μL injection volume. The gradient elution program was verified by methodology to ensure separation efficiency.

[0148] (3) Data preprocessing and metabolite identification

[0149] The original mass spectrometry data was converted into mzXML format by ProteoWizard software, and then the XCMS software package was used for feature peak detection, retention time alignment and drift correction. The feature peaks were screened by strict quality control standards: the signal peaks with a missing rate of >50% were removed, the technical missing values were filled by KNN interpolation method, and the signal intensity was corrected by support vector regression model (SVR). The corrected and screened peaks were identified by searching the laboratory self-built database, integrating public databases, predicting databases and metDNA method. The final screening standard was: metabolite features with annotation comprehensive score ≥0.5 and QC sample coefficient of variation (CV) <30%, and the standardized metabolite matrix (ALL_sample_data) was generated by ion mode integration strategy (retaining the feature ions with the highest qualitative confidence and the best technical repeatability).

[0150] (4) Statistical analysis

[0151] Metabolomics data mining was performed based on the SIMCA analysis platform (version 14.1): principal component analysis (PCA) was used to evaluate the separation trend between groups, and orthogonal partial least squares discriminant analysis (OPLS-DA) was used to screen differential metabolites. Student's t test (for normally distributed data) or Mann-Whitney U test (for non-normally distributed data) was used for univariate analysis, combined with VIP value >1.0 and P<0.05 as the significance standard.

[0152] 12. Data processing and statistical analysis

[0153] The experimental data set was analyzed and processed by the SPSS statistical platform (version 21.0), and scientific visual charts were generated by GraphPad Prism (version 9.4.0) and Adobe Photoshop professional tools. The quantitative indicators were represented as mean ± standard deviation. For variables that meet the normal distribution and have equal variances, Student's t test for independent samples was used for statistical inference. If the variances are not equal, Welch's t test is used, and if the distribution is not normal, Mann-Whitney U test is used. When comparing multiple groups, if the distribution is normal and the variances are equal, one-way analysis of variance (ANOVA) and post-hoc multiple comparisons (Tukey test) are used; if the distribution is not normal or the variances are not equal, Kruskal-Wallis H test and Dunn's post-hoc test are used. The significance level is set to P<0.05 (two-sided).

[0154] The present embodiment is further described in conjunction with the accompanying drawings:

[0155] (I) Effect of hydrogen-rich water on the behavior of mice exposed to chronic aluminum:

[0156] As Figure 1To investigate whether hydrogen-rich water is effective for mice with chronic aluminum exposure, behavioral experiments were conducted on the mice.

[0157] The results of the spontaneous alternation experiment of the Y maze showed that ( Figure 1 A) Compared to the CON group, the number of spontaneous alternations in the AL group was significantly reduced (P<0.05). After intervention, compared to the AL group, the number of spontaneous alternations in the HRW and DFP groups was significantly increased (P<0.05), even approaching the level of the CON group. In the new object recognition experiment ( Figure 1 B), compared to the CON group, the AL group mice showed a significant decrease in novel object exploration time and recognition index (P<0.05). After intervention, the HRW and DFP groups showed a significant increase in novel object exploration time and recognition index compared to the AL group (P<0.05). Open field experiment results showed ( Figure 1 C) Compared with the CON group, the AL group mice had significantly reduced time spent in the central region, number of times they entered the central region, and distance traveled between the central region and the periphery (P<0.05). However, these three indicators were significantly restored in the HRW and DFP groups after intervention (P<0.05).

[0158] (II) Detection of pro-inflammatory factor levels in mouse serum after hydrogen-rich water intervention:

[0159] like Figure 2 Compared to the CON group, the serum levels of pro-inflammatory cytokines interleukin-1β, interleukin-6, and tumor necrosis factor a were significantly increased in the AL group (P<0.05). After drug intervention, the serum levels of pro-inflammatory cytokines interleukin-1β, interleukin-6, and tumor necrosis factor a were significantly decreased in the HRW and DFP groups compared to the AL group (P<0.05). Among them, HRW was significantly more effective than DFP in reducing interleukin-6 (P<0.05).

[0160] (III) Detection of oxidative stress indicators in mouse serum after hydrogen-rich water intervention:

[0161] like Figure 3 Aluminum exposure significantly reduced serum levels of antioxidant markers glutathione and superoxide dismutase in mice (P<0.05), while intervention with HRW or DFP significantly increased these two markers (P<0.05). HRW was significantly more effective than DFP in increasing superoxide dismutase levels (P<0.05).

[0162] (IV) Detection of liver and kidney injury indicators in mice after hydrogen-rich water intervention:

[0163] like Figure 4Compared with the CON group, the AL group mice showed significantly elevated levels of liver tissue damage markers alanine aminotransferase (ALT) and aspartate aminotransferase (AST), as well as kidney damage marker blood urea nitrogen (BUN) (P<0.05). After intervention, the damage markers in the HRW and DFP groups were significantly reduced (P<0.05). These results confirm the liver and kidney protective effect of hydrogen-rich water on mice with chronic aluminum exposure.

[0164] (V) Pathological examination of mouse livers after hydrogen-rich water intervention:

[0165] Mouse liver pathology results as follows Figure 5 As shown, the liver tissue of the CON group mice maintained normal histological structure. Chronic aluminum ion exposure led to pathological damage in the liver of mice, specifically reflected in changes such as inflammatory cell infiltration and loss of liver lobule structural integrity in the liver of the AL group mice. HRW or DFP intervention significantly restored the above-mentioned damage.

[0166] (vi) Detection of β-amyloid protein levels in mouse brain tissue after hydrogen-rich water intervention:

[0167] Changes in brain β-amyloid protein levels, such as Figure 6 As shown in the figure, compared with the CON group, aluminum ion exposure significantly increased the levels of β-amyloid 1-40 and β-amyloid 1-42 in the brain (P<0.05), while HRW or DFP treatment significantly reduced the levels of β-amyloid 1-40 and β-amyloid 1-42 (P<0.05). These results indicate that hydrogen-rich water can reduce β-amyloid deposition induced by chronic aluminum exposure.

[0168] (VII) Detection of the expression levels of tight junction proteins in the brains of mice after hydrogen-rich water intervention at the RNA and protein levels:

[0169] To understand the effects of chronic aluminum exposure on the blood-brain barrier, the expression of tight junction proteins Occludin and ZO-1 in the mouse brain was examined at both RNA and protein levels. Figure 7 The results showed that chronic aluminum exposure significantly reduced the RNA and protein expression levels of the tight junction proteins Occludin and ZO-1 in the mouse brain (P<0.05), while HRW or DFP intervention significantly restored the expression of Occludin and ZO-1 (P<0.05).

[0170] (viii) Detection of intestinal permeability levels in mice after hydrogen-rich water intervention:

[0171] D-lactic acid and diamine oxidase are commonly used to detect intestinal permeability, such as Figure 8Compared with the CON group, the levels of D-lactic acid and diamine oxidase in the serum of mice in the AL group were significantly increased (P < 0.05), and the levels of D-lactic acid and diamine oxidase in the HRW group and the DFP group were significantly lower than those in the AL group after drug intervention (P < 0.05).

[0172] (Nine) Detection of the expression levels of tight junction proteins in the intestines of mice after hydrogen-rich water intervention:

[0173] The expression of tight junction proteins Occludin and ZO-1 in the small intestine of mice was further detected at the RNA level and the protein level. As shown in Figure 9 , aluminum exposure can significantly reduce the RNA and protein expression levels of tight junction proteins Occludin and ZO-1 in the small intestine of mice (P < 0.05), while HRW or DFP intervention can significantly restore the expression of Occludin and ZO-1 (P < 0.05). This further indicates that aluminum exposure can damage the intestinal barrier, and HRW can play a protective role.

[0174] (Ten) Beta diversity analysis of intestinal flora after hydrogen-rich water intervention:

[0175] Aluminum exposure can affect the composition of intestinal flora, and hydrogen-rich water is also known to have a great impact on the intestinal microecology of organisms. In order to study whether hydrogen-rich water can affect the intestinal flora of aluminum-exposed mice, fecal metagenomic sequencing was performed on a total of 15 samples from the three groups.

[0176] In order to explore the similarity or difference in species composition between groups, Beta diversity analysis was performed on the samples. The closer the scatter points of related samples, the more similar the species composition between samples. As shown in Figure 10 A, principal component analysis can be obtained, and the scatter points representing the CON group, the AL group and the HRW group are separated, wherein the scatter point coordinates distance between the HRW group and the CON group is closer than that between the AL group and the CON group, and the difference is smaller. This result is further verified in the principal coordinate analysis Figure 10 B), suggesting that the species composition of the intestinal flora of the HRW group mice tends to be closer to that of the CON group.

[0177] (Eleven) Species composition analysis of intestinal flora after hydrogen-rich water intervention:

[0178] In order to more intuitively see the composition structure of the flora between groups, the top 30 communities in relative abundance were analyzed at the genus level and the species level, respectively. At the genus level Figure 11 A), Prevotella, Lactobacillus and Bacteroides have higher abundance and belong to dominant genera. At the species level Figure 11 B), Lachnospiraceae bacterium, Muribaculaceae bacterium-isolate 037 (Hiran), Lachnospiraceae bacterium A4 strain and Lactobacillus rhamnosus have higher abundance.

[0179] (xii) Analysis of the differences in gut microbiota after hydrogen-rich water intervention:

[0180] LEfSe analysis identified the differences in gut microbiota of each group at multiple taxonomic levels, using LDA score >3 as the screening standard for potential biomarkers Figure 12 A). Meanwhile, the top 30 communities in terms of genus level and species level abundance were analyzed for differences, and the results were as follows Figure 12 B-C): Compared with the CON group, the abundance of the genus level community Bacteroides, Dubosiella, Prevotella and the species level community Mus Duobus, Prevotella_sp. MGM2 species in the AL group mice decreased significantly (P<0.05). Compared with the AL group, the abundance of the genus level community Clostridium, Roseburia, Streptococcus and the species level community Oleic Acid Bacteroides, Fecal Bacteroides, Lachnospira_bacteria_MD335, Prevotella_sp. MGM2, Roseburia_sp. CAG:303 in the HRW group mice increased significantly (P<0.05).

[0181] (xiii) Non-targeted metabolome sequencing analysis of mouse feces:

[0182] As shown in Figure 13 , based on the three-dimensional results of PCA and the score plot of orthogonal partial least squares discriminant analysis, it can be seen that the metabolites from samples of different groups are largely separated, indicating that there are different metabolic patterns between different groups.

[0183] The relationship between the differential metabolites between groups is shown in the form of a Venn diagram. As shown in Figure 14 A), a total of 191 differential metabolites were detected between the AL and CON groups, while 771 differential metabolites were detected between the HRW and AL groups, and 60 differential metabolites were detected between the three groups. The top 50 differential metabolites in the AL group compared with the CON group and the HRW group compared with the AL group were shown by a heatmap Figure 14C-D). As shown by the heat map, compared with the CON group, the levels of d-camphoric acid, ethyl octadecatetraenoate, 6-ethylthiopurine, N1-acetylneuraminic acid, epigoitrin, soyasapogenol B, tanespimycin, prostaglandin D2-d9, ethyl octadecatetraenoate, and entecavir were significantly reduced (P < 0.05), and the level of geosmin was significantly increased (P < 0.05) in the AL group. However, compared with the AL group, the levels of baicalein, mupirocin, and indole-3-ethanol were significantly increased (P < 0.05), and the levels of exsulind A, 3-nitrotyrosine, geosmin, 3-oxooctadecanoic acid ethyl ester, and pahu toxin were significantly reduced (P < 0.05) after HRW intervention. Among the common differential metabolites, it was found that indomethacin had a reduced level in the AL group, but an increased level in the HRW intervention group; 3-nitrotyrosine had an increased level in the AL group, but a decreased level in the HRW intervention group Figure 14 B).

[0184] (Fourteenth) Correlation analysis between intestinal flora and biomarkers:

[0185] To explore the relationship between the changes in intestinal flora and the body's inflammatory response, oxidative stress, and other factors, a correlation analysis between the differential flora and biochemical indicators was performed. As shown in FIG. (8), Figure 15 ), Bacteroides, Dubosiella, Prevotella_sp._MGM2, and other species were negatively correlated with the levels of beta-amyloid 1-40 and beta-amyloid 1-42; Roseburia was negatively correlated with the levels of diamine oxidase, D-lactic acid, and pro-inflammatory factors interleukin 6, interleukin 1 beta, and tumor necrosis factor a, and was positively correlated with the level of glutathione. Bacteroides oleiciresinibacter and Bacteroides stercoris were negatively correlated with the levels of beta-amyloid 1-40, beta-amyloid 1-42, diamine oxidase, D-lactic acid, interleukin 6, and interleukin 1 beta, and were positively correlated with the levels of glutathione and superoxide dismutase. Lachnospira_bacterium_MD335 was negatively correlated with the levels of DAO diamine oxidase, D-lactic acid, interleukin 6, interleukin 1 beta, and tumor necrosis factor a, and was positively correlated with the levels of glutathione and superoxide dismutase.

[0186] (Fifteenth) Correlation analysis between intestinal flora and metabolites:

[0187] To further explore the relationship between intestinal flora and differential metabolites, a multi-omics correlation analysis was performed. As shown in FIG. (9), Figure 16 A), indomethacin was positively correlated with Bacteroides and Prevotella_sp._MGM2. In the correlation analysis related to N-acetylneuraminic acid, it was positively correlated with Bacteroides and Prevotella_sp._MGM2; in addition, soyasapogenol B was positively correlated with Bacteroides, Dubosiella, Mus-Dubosiella, and Prevotella_sp._MGM2.Figure 16 As shown in B, baicalein is positively correlated with the species of Roseburia, Bacteroides oleaticus, Bacteroides stercoris, Lachnospira_bacterium_MD335, and Prevotella_sp._MGM2; indole-3-ethanol is positively correlated with the species of Dubosiella, Mus dubosiella, and Prevotella_sp._MGM2; and 3-oxooctadecanoic acid ethyl ester is negatively correlated with the species of Roseburia, Bacteroides oleaticus, Bacteroides stercoris, Lachnospira_bacterium_MD335, Prevotella_sp._MGM2, and Roseburia_sp._CAG:303.

[0188] The above description of the present application and its embodiments is not restrictive, and the embodiments shown in the drawings are only one of the embodiments of the present application, and the actual structure is not limited thereto. In general, if a person skilled in the art is inspired by it, without departing from the purpose of the present application, without creative design, similar structure and embodiments of the technical solution can be designed, which should belong to the protection scope of the present application.

Claims

1. The application of hydrogen-rich water in improving chronic aluminum exposure injury in mice, characterized in that, The damage caused by chronic aluminum exposure includes at least one of nerve damage, liver and kidney damage, intestinal barrier damage, and blood-brain barrier damage.

2. The application according to claim 1, characterized in that, The product is a beverage, health supplement, or medicine.

3. The application according to claim 1, characterized in that, The improvement is achieved by regulating the gut-microbe axis, including upregulating the abundance of beneficial gut bacteria such as Roche and Bacteroides, and downregulating the oxidative metabolite 3-nitrotyrosine.

4. The application according to claim 3, characterized in that, The regulation includes increasing the levels of the anti-inflammatory metabolites baicalin and indole-3-ethanol, and decreasing the expression of inflammatory factors interleukin-6, interleukin-1β, and tumor necrosis factor a.

5. A pharmaceutical composition for improving chronic aluminum exposure injury in mice, characterized in that: It contains hydrogen-rich water as the active ingredient and a pharmaceutically acceptable carrier.

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