Alcoholic Metabolic Activation in Mice: The Role of A Small Cluster Mineral Water

Alcoholic Metabolic Activation in Mice: The Role of A Small Cluster Mineral Water | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Alcoholic Metabolic Activation in Mice: The Role of A Small Cluster Mineral Water Hui Zhang, Ming Wang, Han Qi, Yuwei He, Maichao Li, Hailong Li, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7390244/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 13 You are reading this latest preprint version Abstract To explore the molecular mechanisms underlying the effects of a specific small cluster mineral water (C-cell mineral water) on ethanol metabolism, we conducted a series of assessments comprising anti-acute alcohol toxicity experiments including behavioral hangover responses, serum ethanol levels, liver activities of alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH), along with metabolomic and transcriptomic analyses within 24h, and anti-chronic alcohol toxicity experiments including analysis of liver catalase (CAT) activity, along with metabolomic and transcriptomic profiling after 21d intervention of ethanol accompany with C-cell mineral water. The results suggested that the C-cell mineral water significantly delayed the latency of drunken and decreased the duration of drunken in mice, simultaneously reduced serum ethanol level at 3h and 4h. It also enhanced liver ADH and ALDH activities at 2h and activated CAT activity at 21d, compared to purified water. Transcriptomic analysis revealed that some genes related to ethanol metabolism including CYP450s , ALDH3B3 , and SULT5A1 were up-regulated. Additionally, the metabolomic analysis identified that the most significantly altered pathways included primary bile acid biosynthesis, various drug metabolism pathways, and CYP450-mediated drug metabolism. Subnetworks with maximum changes featured interactions between pathways of oxidative phosphorylation, arginine biosynthesis, and primary bile acid biosynthesis, etc. The results showed that the effect of C-cell mineral water was better than that of purified water on relieving drunken, which could accelerate the conversion of acetaldehyde to acetate, and ultimately metabolize into CO 2 and H 2 O through TCA cycle. These findings will provide innovative strategies for preventing acute alcoholism and relieving chronic alcohol toxicity. Biological sciences/Biochemistry Biological sciences/Molecular biology alcohol metabolism small cluster mineral water alleviation of alcohol toxicity Figures Figure 1 Figure 2 Figure 3 1. Introduction Water is the most abundant component in the human body, comprising a substantial percentage of an individual body weight across different age groups: children (65–75%), adults (55–60%), and the elderly (50%) 1 . Many kinds of mineral water available in the market are widely recognized for health benefits. While numerous reports have extolled the virtues of natural mineral water for health 2 , 3 , there has been little attention given to the specific benefits of small cluster mineral water. C-cell mineral water originates from the mineral-rich Changbai Mountain region in Jilin Province, China. It is naturally weakly alkaline with a pH of 8.5 ± 0.5 and contains an array of minerals and trace elements, including lithium, strontium, zinc, and selenium. This makes it a valuable source of essential nutrients for human consumption. What distinguishes C-cell mineral water is its unique small cluster structure, which is achieved through innovative technology. The cutting-edge reactor, composed of nano-scale ion sieve materials derived from silicate crystal minerals, has the capability to alter the dynamic hydrogen bond network system within water cluster groups. This modification weakens or disrupts the hydrogen bonds between water molecules, resulting in the decomposition of large clusters containing 13–15 water molecules into smaller clusters comprising only 6 water molecules. Through long-range strong magnetic induction facilitated by the reforming reactor, the most stable configuration for hydrogen bonding is achieved with a linear arrangement of six-ringed water molecules 4 (patent number: ZL201410440053.5, ZL201310384523.6). Small cluster water can induce rapid expansion and gradual contraction of cell. Rapid expansion can ensure that there is sufficient water within the cells to maintain the activity of enzymes, substance transport, and normal physiological activities. It also can increase the surface area of cells, enhancing the efficiency of material exchange between cells and the external solution 5 . Our prior study has demonstrated that consuming C-cell mineral water for 12 weeks improved metabolism and enzyme activity in mice, potentially reducing the risk of obesity 6 . Alcohol consumption is a prevalent global practice. While moderate intake may offer cardiovascular benefits, chronic and excessive drinking can precipitate a spectrum of health issues, including liver diseases, cardiovascular diseases, dementia, various cancers, and even mortality 7 , 8 . Ethanol, the primary component of alcoholic beverages, is intoxicating but not directly toxic; its metabolites are the culprits behind the associated health risks. Understanding ethanol metabolism is crucial for unraveling the pathophysiological mechanisms of alcohol-related harm 9 , 10 . Ethanol is primarily absorbed in the stomach (22%) and intestine (75%) and is metabolized in the liver into acetaldehyde and acetic acid (~ 95%) 8 . This metabolic process also leads to an increase in reactive oxygen species (ROS) and a decrease in the NAD + /NADH ratio. Ethanol metabolism involves two pathways: oxidation and non-oxidative metabolism. The majority of ethanol (80%-90%) is metabolized to acetaldehyde by cytosolic alcohol dehydrogenase (ADH), leading to the generation of NADH 11 . The microsomal pathway, involving the cytochrome P450 (CYP) family, accounts for about 10% of ethanol metabolism, with CYP2E1 being a key enzyme. This enzyme converts ethanol into acetaldehyde, producing reactive oxygen species (ROS) that contribute significantly to alcohol's toxicity 12 . Catalase (CAT), an enzyme found in peroxisomes, also participates in ethanol metabolism, generating ROS and converting ethanol directly into acetaldehyde and water 12 . The acetaldehyde produced is then oxidized by aldehyde dehydrogenase (ALDH) to form acetic acid 13 , a rate-limiting step in alcohol's oxidative metabolism. Acetic acid is further converted into acetyl-CoA, which can enter the tricarboxylic acid cycle or engage in other metabolic processes. The activity of various ADH and ALDH isoforms regulates acetaldehyde concentrations, influencing the risk of alcoholism. The effects of ethanol intolerance, such as nausea, dysphagia, headache, and facial flushing, have been linked to acetaldehyde levels. The accumulation of this metabolite in individuals with inactive or poorly active ALDH isoenzymes may explain cultural aversions to heavy drinking in some societies. Ethanol can also undergo non-oxidative metabolism, with minor pathways converting it into ethyl sulfate (EtS) via sulfotransferases (SULTs), ethyl glucuronide (EtG) through uridine diphosphate (UDP)-glucuronosyltransferase (UGT), fatty acid ethyl esters (FAEEs) by fatty acyl synthases, and phosphatidylethanol (PEth) by replacing choline in phosphatidylcholine (PC) 8 (Fig. 3-A). Anti-alcoholic drugs may alleviate the symptoms of intoxication but do not address the underlying damage caused by alcohol. Current anti-alcoholic medications encompass chemical medications, traditional Chinese medicine, and health care products containing active ingredients such as peptides, proteins, honey, vitamins, lactic acid protein, and microbial products 14 . However, there is no evidence to suggest that natural mineral water could mitigate alcohol-induced harm. This study aims to explore the potential anti-alcoholic effects of C-cell small cluster mineral water in mice. 2. Animals and Methods 2.1 Animals and Experimental Design We procured male C57BL/6J mice, aged 6–8 weeks with an average body weight of 20 ± 2 grams, from Jinan Pengyue Company. Following a one-week acclimatization period, the mice were randomly assigned into four groups based on the intervening measure outlined in Table S1 . The intervention included C-cell mineral water (Tasly, Jilin, China), Changbaishan mineral water, RU21, and purified water. The ethanol intervention used Guotai liquor of 53%vol (Guizhou, China). The anti-acute alcohol toxicity experiment within 24h administered twice the above types of drinks at 30 minutes prior to and 5 minutes after the ethanol challenge with a dosage of 13 mL/kg through gavage. The anti-chronic alcohol toxicity experiment extended over 21 days provided with the above types of drinks ad libitum (all day long) and with an alcoholic dosage of 7 mL/kg once a day (Supplementary Material Table S1 ). The proposed experimental flow chart is outlined below in Fig. 1-A. All mice were euthanized by CO 2 . All methods involving experimental animals were performed in accordance with the ARRIVE guidelines and relevant institutional and national regulations, and were approved by the Institutional Animal Care and Use Committee of Qingdao University (Approval No.QDU-AEC-2024689). 2.2 Detection of Behavioral Indicators of Drunken Four types of drinks including C-cell mineral water, Changbaishan mineral water, RU21, and purified water were given twice to the mice at a dosage of 11 mL/kg, 30 minutes prior to and 5 minutes after the ethanol intervention via gavage. Post ethanol intervention, a subset of 10 mice was randomly selected to monitor behavioral indicators of intoxication, including the drunken latency, duration of drunken over a 24-hour period. 2.3 Detection of Serum Ethanol Content Mice were fed with the above four types of drinks twice at 30 minutes prior to and 5 minutes after the ethanol intervention via gavage, with a dosage of 13 mL/kg. At various time points post ethanol intervention (30, 60, 90, 120, 180, 240, and 300 minutes), serum samples were collected from six mice at each time point. The serum ethanol concentration was promptly measured within 30 minutes using the Ethanol Colorimetric Assay Kit (Elabscience, Wuhan, China). 2.4 Activity of ADH、ALDH and CAT in Liver The same intervention was followed as in Section 2.1. After a 120 minutes interval post ethanol intervention, serum samples from six mice at each time point were collected to measure the activities of ADH and ALDH. These enzyme activities were determined using the ADH Activity Assay Kit (Colorimetric) (Abcam, Shanghai, China) and the ALDH Activity Assay Kit (Colorimetric) (Abcam, Shanghai, China), respectively. Following a 21-day chronic alcohol toxicity experiment with a dosage of 7 mL/kg, the activity of CAT was assessed in eight mice per group using the CAT Activity Assay Kit (Elabscience, Wuhan, China). 2.5 Liver Transcriptomic Analysis Liver tissue samples (25 mg per mouse) were collected from three mice per group (in two groups of C-cell mineral water and Changbaishan mineral water) at 1h, 2h, 3h, and 21d after the alcohol intervention, described as in Section 2.1. Total RNA extracted from the liver was subjected to high-throughput sequencing using the MGISEQ-2000RS platform (Metware, Wuhan, China). Detailed procedures for library preparation, sequencing, and differential analysis are outlined in the Supplementary Material Text S1. 2.6 Liver Metabolomic Analysis To comprehensively map the metabolic changes, liver tissue samples (25 mg) from each mouse (with six mice per group selected in two groups of C-cell mineral water and Changbaishan mineral water) were analyzed using a modified method from Wu et al., with certain distinctions noted 15 . The metabolomic profiling was carried out by UPLC-MS through the services of Metware Biotechnology Co., Ltd. (Wuhan, China). The Supplementary Material Text S2 outlines the detailed methodologies for extraction, identification, and data analysis. Rigorous quality control procedures were implemented to ensure the accuracy and precision of the metabolomic data. 2.7 Statistical Analysis One-way and two-way ANOVA followed by Tukey post-hoc testing was conducted to assess statistical significance ( P < 0.05). The analysis method of transcriptomic and metabolomic data are presented in the Supplementary Material. For KEGG, we get permission to use the KEGG software from the Kanehisa laboratory 16 , 17 . 3. Results 3.1 Behavioral Indicators of Drunken Our findings indicated that the latency of drunken for mice in groups of C-cell mineral water and RU21 were significantly extended compared to those in the groups of purified water and Changbaishan mineral water ( P < 0.05) (Fig. 1-B). Additionally, the duration of drunken for the C-cell mineral water and RU21 groups were markedly reduced compared to other drinks groups ( P < 0.05) (Fig. 1-C) (Supplementary Material Table S2 ). These results suggested that the C-cell mineral water group exhibited a significantly superior performance in terms of the drunken latency and the speed of sobering up in terms of duration of drunken compared to the purified and Changbaishan mineral water ( P < 0.05). 3.2 Serum Ethanol Levels The serum alcohol content in C-cell mineral water group was significantly lower than that of in purified water group at 3h and 4h ( P < 0.05) (Fig. 1-F), and serum alcohol level in RU21 group was significantly lower than that of in purified water group at 1h, 1.5h, 2h, 3h and 4h ( P < 0.05) (Fig. 1-F). The results showed that the effect of C-cell mineral water was better than that of purified water on relieving drunken. 3.3 Activity of ADH、ALDH and CAT Two hours post alcohol intervention, the activity of the ADH enzyme in the C-cell mineral water group was 1.72 times higher than in the purified water group ( P < 0.05) (Fig. 1-D), and the ALDH enzyme activity was 1.29 times higher than in the purified water group ( P < 0.05) (Fig. 1-E), indicating a significant enhancement compared to the purified water group. No significant differences were observed at other time points. Upon continuous alcohol intervention over a 21-day period, the CAT activity in the C-cell mineral water group was notably higher than in other groups, suggesting that C-cell mineral water has the potential to enhance CAT enzyme activity ( P < 0.05) (Fig. 1-G). 3.4 Transcriptomic Differences By employing transcriptomic analysis with a stringent screening criteria of false discovery rate (FDR) < 0.05 and |log 2 Fold Change| ≥1, we identified a total of 1462 differential expressed genes (DEGs) across four time points (1 h, 2 h, 3 h, and 21 d). The volcano plots visually depicted these changes, revealing distinct expression patterns between the C-cell mineral water and Changbaishan mineral water group. Specifically, at the 1h mark, 288 genes were up-regulated and 148 genes were down-regulated (Fig S1 -A). At the 2h mark, these numbers were 264 up-regulated and 211 down-regulated (Fig S1 -C). At the 3h point, 182 genes were up-regulated and 170 down-regulated (Fig. 2-A). Finally, at the 21d, 89 genes were up-regulated and 110 were down-regulated (Fig S1 -E). Enrichment analysis based on KEGG pathways highlighted several significantly enriched pathways, including metabolic pathways, the PPAR signaling pathway, fatty acid metabolism, inflammatory mediator regulation of TRP channels, and bile secretion (Fig. 2-B, Fig S1 -B, S1-D, S1-F). Notably, genes associated with ethanol metabolism, such as CYPs , ALDH3B3 , and SULT5A1 , exhibited significant up-regulation, underscoring their potential roles in the observed physiological responses. 3.5 Metabolic Profiling Differences We conducted a comprehensive untargeted metabolomics analysis, discovering a total of 5489 metabolites across both positive and negative ionization modes at the four time points (1h, 2h, 3h, and 21d). Principal component analysis (PCA) was utilized to assess the intrinsic metabolic variations and the quality of the data. The PCA results demonstrated a distinct separation trend between the C-cell mineral water and the Changbaishan mineral water group, suggesting that the metabolic profiles effectively differentiated the two groups at all time points. Additionally, the quality control samples were tightly clustered, attesting to the instrument's repeatability and stability (Fig S2 -A, B, C, D). To gain further insights into the metabolic profiling characteristics, orthogonal partial least squares discriminant analysis (OPLS-DA) was employed. This analysis revealed pronounced separation between the C-cell mineral water group and Changbaishan mineral water group, underscoring the significant metabolic profile differences between the two groups (Fig. 2-C, Fig S4-A, Fig S5-A, Fig S6-A). Moreover, the permutation test results, which were repeated 200 times, confirmed that the four OPLS-DA models were well-fitted without any indication of overfitting (Fig S3 -A, B, C, D). 3.5.1 Metabolic Profiling Comparison at 1h Post Intervention Between C-cell and Changbaishan Mineral Water Groups A t-test was employed to identify differential metabolites between the two groups, revealing a total of 227 metabolites with FDR <0.05. As depicted in the volcano plot (Fig S4-B) and detailed in Supplementary Table S3 , the C-cell mineral water group exhibited that 226 metabolites were down-regulation (with FDR < 0.05 and Fold change (FC)<3/4), and 1 metabolite was up-regulation (with FDR 4/3). All differential metabolites were subsequently subjected to clustering analysis (Fig S4-C). Quantitative Enrichment Analysis (QEA) using global tests uncovered that the predominantly dysregulated metabolic pathways encompassed drug metabolism involving other enzymes, CYP450-mediated drug metabolism, galactose metabolism, glycerolipid metabolism, and sphingolipid metabolism (Fig S4-D). Recognizing that metabolic pathway enrichment analysis might not fully capture the overall, topological, and inter-pathway disruptions, we implemented the Network Propagation-based Algorithm called as FELLA. This advanced algorithm ingested differential metabolites and assessed the impact at each node (metabolites, enzymes, reactions) and each edge (their hierarchical connections) to pinpoint the most significantly perturbed subnetwork. Utilizing this approach, we identified that the interplay among apoptosis, neoptosis, Fc gamma R-mediated phagocytosis, GnRH signaling pathway, and asthma pathways constituted the most significantly affected sub-networks (Fig S4-E). 3.5.2 Metabolic Profiling Comparison at 2h Post Intervention Between C-cell and Changbaishan Mineral Water Groups The application of t-test analysis discovered 314 differential metabolites with FDR4/3), while 312 metabolites were down-regulated (with FC<3/4) (Fig S5-B and Table S4). Fig S5-C presented the clustering analysis of these differential metabolites, revealing distinct patterns of metabolic regulation. QEA analysis of the metabolic pathways implicated that the most affected pathways included primary bile acid biosynthesis, the pentose phosphate pathway, glycerophospholipid metabolism, as well as drug metabolism involving other enzymes and the cytochrome P450 pathway (Fig S5-D). Further analysis based on FELLA indicated that the dysregulated metabolic subnetworks were predominantly associated with oxidative phosphorylation, bile secretion, and linoleic acid metabolism, suggesting a complex interplay of metabolic responses perturbations in these groups (Fig S5-E). This analysis provideed a deeper understanding of the metabolic shifts occurring at the 2h mark post intervention, highlighting the divergent effects of C-cell and Changbaishan mineral water on the metabolic profiles. 3.5.3 Metabolic Profiling Comparison at 3h Post Intervention Between C-cell and Changbaishan Mineral Water Groups Employing t-test analysis based on FC, we identified 210 differential metabolites between the two groups. In comparison to the Changbaishan mineral water group, the C-cell group exhibited 14 up-regulated metabolites and 196 down-regulated metabolites (Fig. 2-D and Table S5). A cluster analysis of these metabolites revealed a distinct separation in the heatmap (Fig. 2-E). The disturbed metabolic pathways primarily involved steroid biosynthesis, fatty acid degradation, fatty acid elongation, drug metabolism involving other enzymes, cytochrome P450-mediated drug metabolism, caffeine metabolism, and arginine biosynthesis (Fig. 2-F). The analysis of disturbed metabolic subnetworks indicated a concentration in arginine biosynthesis and linoleic acid metabolism (Fig. 2-G). 3.5.4 Metabolic Profiling Comparison at 21d Post Intervention Between C-cell and Changbaishan Mineral Water Groups The metabolite volcano plot depicted 103 metabolites with FDR<0.05, with 11 up-regulated and 92 down-regulated (Fig S6-B and Table S6)). In alignment with previous comparisons, a heatmap of significantly differential metabolites showed clear separation between the two groups (Fig S6-C). Enriched metabolic pathways included steroid hormone biosynthesis, sulfur metabolism, sphingolipid metabolism, primary bile acid biosynthesis, drug metabolism involving other enzymes, cytochrome P450-mediated drug metabolism, and cysteine and methionine metabolism (Fig S6-D). The disturbed metabolic subnetworks were predominantly composed of steroid biosynthesis, primary bile acid biosynthesis, lysine degradation, D-amino acid metabolism, Fc gamma R-mediated phagocytosis, and the GnRH signaling pathway (Fig S6-E). 3.6 Integrated KEGG Pathway Analysis of Metabolome and Transcriptome In order to investigate the impact of C-cell mineral water on alcohol metabolism, a comprehensive KEGG pathway analysis was conducted on the annotated genes and metabolites associated with alcohol metabolism. The results revealed that 64 genes and 5 metabolites were involved in alcohol metabolism. Although some genes and metabolites did not show statistically significant differences, their trends within alcohol metabolism pathways were observable. Specifically, the ALDH gene exhibited an up-regulation trend following the intervention of C-cell mineral water at 1 h, 2 h, and 21 d (Fig S4-F, Fig S5-F, Fig S6-F). Similarly, the CYP2E1 gene showed an up-regulation trend after 2h and 3h of C-cell mineral water intake (Fig S5-F, Fig. 2-F). The metabolite NAD + consistently showed up-regulation across all four time points (1h, 2h, 3h, and 21d) (Fig S4-F, Fig S5-F, Fig S6-F, Fig. 2-F), while NADP + was down-regulated at 1h but up-regulated at 21d (Fig S4-F, Fig S6-F). Additionally, pathways such as AMPK signaling and fatty acid biosynthesis were found to be perturbed by the intervention. 4. Discussion Intoxication occurs when a high concentration of alcohol in the bloodstream rapidly reaches the brain, causing it to transition from a state of excitement to inhibition. This shift leads to uncontrolled excitement in the subcortical centers of brain, resulting in a cascade of effects that disrupt cognition, judgment, and motor functions. The most immediate behavioral change is the loss and subsequent recovery of the righting reflex, a key indicator of inebriation. RU21 hangover pill, a popular hangover-relief product with origins in Russia, has made a significant impact on the international market. Its core ingredient is a natural extract, complemented by essential nutrients such as vitamin C, glucose, and glutamic acid. RU21 functions by accelerating alcohol metabolism, specifically by slowing the oxidation of alcohol into the toxic acetaldehyde and facilitating the conversion of acetaldehyde into the less harmful acetate. Its efficacy has been previously reported, and it is commonly used as a positive control in such studies 18 . In our investigation of anti-acute alcohol toxicity effects within a 24h window, we compared the hangover-relief effects of different drinks. The C-cell mineral water presented a better anti-hangover effect comparable to that of RU21 (Fig. 1). Our findings indicated that the enzymic activities of ADH and ALDH were significantly induced at 2h after alcohol intervention in the group fed with C-cell mineral water, as compared to the purified water group (Fig. 1-D, E). Additionally, the serum ethanol concentration at 3h and 4h marks post-intervention was significantly lower in the C-cell mineral water group, suggesting a hangover-relief effect compared with RU21 (Fig. 1-F). We hypothesized that C-cell small cluster water may enhance the metabolism of ethanol by boosting the activity of ADH and ALDH, thereby reduced the concentration of acetaldehyde and promote its conversion. Regarding the anti-chronic alcohol toxicity effects, the CAT activity in the C-cell mineral water group was significantly higher than in the control group, indicating that C-cell mineral water offers a degree of protection against chronic alcohol-induced damage. Previous studies conducted by Vitali and Wang have indicated that mineral water has the potential to increase diuresis, aid in the elimination of waste products, prevent urinary stones, and exhibit anti-inflammatory and anti-infective properties 2 , 19 . Our study contributed to the understanding of the potential protective effects of C-cell mineral water against alcohol toxicity, highlighting its ability to mitigate both acute and chronic alcohol-related harm, and emphasizing the need for further research into the role of mineral water components in alcohol metabolism and detoxification. The cytochrome P450-mediated drug metabolism pathway was significantly enriched across all four time points (1h, 2h, 3h, and 21d) following C-cell water intervention, as determined by KEGG pathway enrichment analysis of the metabolic profiles, in comparison to the control group. CYP450 enzymes played a crucial role in the metabolism of a wide range of compounds, including drugs, steroids, and vitamins. The connection between human P450s and disease was a subject of considerable interest, particularly the impact of single nucleotide polymorphisms that may result in nonfunctional enzyme variants and contribute to disease pathology 20 . CYP2E1, a key enzyme in ethanol metabolism, was of particular interest. In some individuals, a significant portion of CYP2E1 was found in the mitochondria 21 . CYP2E1 shared its role in ethanol oxidation with two other enzymes, ADH and CAT 20 , 22 . CYP2E1 was recognized for its affinity towards small molecules, such as anesthetics 23 . It was now understood that several human CYP450s operate primarily through a conformational selection mechanism. Research by Scott and colleagues has shed light on the structural aspects of CYP2E1, with the publication of X-ray crystal structures that revealed the enzymic interactions with both small ligands and larger molecules, such as fatty acids 24 , 25 . The catalytic mechanism of ethanol oxidation by CYP2E1 involved a series of well-defined steps: substrate binding, reduction of ferric iron to ferrous, binding of molecular oxygen, introduction of a second electron into the iron-oxygen complex, transformation of the complex to Compound I (FeO 3+ ), abstraction of a hydrogen atom, oxygen rebound, and finally, product release 26 . These insights into the molecular details of CYP2E1 function were invaluable for understanding its role in ethanol metabolism and its potential implications for health and disease. The drug metabolism-other enzymes pathway was significantly enriched across all four time points (1h, 2h, 3h, and 21d) following C-cell water intervention, as revealed by KEGG pathway enrichment analysis of the metabolic profiles. This pathway encompassed a variety of metabolic enzymes involved in ethanol metabolism, including alcohol dehydrogenases such as ADH, ALDH, CYP2E1, and CAT, as well as non-oxidative metabolizing enzymes like SULTs, UGTs, and FAEES 8 . In the C-cell mineral water group, the transcriptional expression of SULT5A1 was notably up-regulated at 3h after alcohol intervention when compared to the control group. SULTs facilitated the transfer of a sulfate group from the cofactor 3'-phosphoadenosine 5'-phosphosulfate to substrates containing a hydroxyl (OH) group, playing a pivotal role in the homeostasis of endogenous compounds, which included hormones, neurotransmitters, and bile acids 27 . SULTs constituted a substantial family of enzymes, categorized into six families ( SULT1-SULT6 ) 28 . Research has indicated that the gene expression of SULT5A1 was regulated in conjunction with the homeostasis of bile acids in mice subjected to a high-fat diet, with this regulation occurring in an age-dependent manner 29 . Furthermore, investigations into the processing of drug-metabolizing genes following the pharmacological activation of xeno-sensors, such as 2,3,7,8-tetrachlorodibenzodioxin (TCDD), have demonstrated an increase in the mRNA expression of SULT5A1 . This highlights the potential role of SULT5A1 in the metabolic response to alcohol and its modulation by external stimuli 30 . Following 21d of alcohol treatment, the transcriptional expression of ALDH3B3 was found to be up-regulated in the C-cell mineral water group in comparison to the control group. ALDHs are crucial enzymes that catalyze the conversion of toxic aldehydes into harmless carboxylic acids, playing a vital role in detoxification processes. The human genome is known to contain 19 distinct ALDH genes, while the mouse genome harbors 21 ALDH genes 31 , 32 . The ALDH3 family, which includes ALDH3A1 , ALDH3A2 , ALDH3B1 , ALDH3B2 , and ALDH3B3 , is particularly responsible for the detoxification of lipid-derived aldehydes. Among the various ALDH families, the ALDH3 genes exhibit the most significant variation in number across different organisms. Both the mouse and rat ALDH3B3 proteins are classified within the ALDH3B2 clade 31 . It has been hypothesized that ALDH3B2 functions to eliminate lipid-derived aldehydes that accumulate in lipid droplets as a consequence of oxidative stress, thereby serving as a quality control mechanism 32 . The up-regulation of ALDH3B3 after C-cell mineral water intake suggested a potential enhancement on the body capacity to process and mitigate the toxic effects of lipid-derived aldehydes, which could be particularly beneficial in the context of alcohol metabolism and its associated health implications. This highlighted the importance of further investigating the role of ALDH3B3 and the modulation of its expression in alcohol metabolism and detoxification pathways. The primary bile acid biosynthesis pathway exhibited significant changes at both the 2h and 21d marks after alcohol intervention in the C-cell mineral water group when compared to the control group. Bile acids (BA), which include both primary and secondary types, are acknowledged as agonists for a variety of receptors. Within the enterohepatic circulation, bile acids have the capacity to enter the systemic circulation, where they can transmit metabolic signals to almost all organs. This is achieved by binding to and activating specialized bile acid receptors, thus modulating the organism physiological metabolic state. It has been documented that ethanol intake can up-regulate the expression of enzymes related to BA synthesis (such as Cyp7a1, Cyp27a1, Cyp8b1, and Baat) and transporters, while concurrently down-regulated the expression of Na + -taurocholate cotransporting polypeptides (NTCPs) and the Farnesol X receptor (FXR) in the ileum and liver, respectively 33 . This suggested a complex regulatory interplay between ethanol metabolism and bile acid homeostasis. Studies by Brandl et al. have reported significantly elevated levels of total and conjugated BAs in patients diagnosed with alcoholic hepatitis 34 . This finding underscored the connection between alcohol-induced liver stress and BA metabolism. Furthermore, researchers have observed that ethanol consumption lead to alterations in intestinal BA metabolism 8 , 35 , which may have broader implications for gut health and liver function in alcohol consumption. These observations collectively highlighted the intricate relationship between alcohol metabolism and BA regulation, indicating that modulation of BA synthesis and transport may play a crucial role on response to alcohol metabolism and could be a potential target for preventing alcohol induced health problem. Activation of peroxisome proliferator-activated receptor alpha (PPAR-α) can shift ethanol metabolism from the CYP2E1 pathway, which produced reactive oxygen species (ROS), to the peroxidase pathway, which eliminated ROS, thereby facilitating alcohol elimination 36 . Our study observed an increase in PPAR-α expression at 2h and 3h after alcohol intervention, indicating that C-cell mineral water may protect against alcohol toxicity by up-regulating the PPAR-α gene. Additionally, our results suggested that NAD + metabolite was up-regulated through the AMPK signaling pathway in the C-cell mineral water group at all time points. Previous research has shown that the PPARα-CAT pathway played a crucial role in regulating NAD + synthesis enzymes, maintaining NAD + /NADH redox balance, and accelerating alcohol and H 2 O 2 detoxification in mice 36 . We postulated that the potential mechanism of small cluster mineral water is to suppress oxidative stress production, comprehensively enhance alcohol metabolism, and exert a significant anti-alcohol effect. We proposed that the potential mechanism of the small cluster mineral water exerts its effects by suppressing oxidative stress production and comprehensively enhancing alcohol metabolism, thereby exerting a significant protective effect against alcohol-induced damage. This suggested that C-cell mineral water may offer a novel and potentially effective strategy for mitigating alcohol toxicity and promoting metabolic homeostasis. As previously discussed, traditional metabolic pathway enrichment analysis may not fully capture the comprehensive, topological, and inter-pathway interactions. To address this limitation, we utilized network propagation-based algorithms to further elucidate the impact of C-cell mineral water on metabolic processes. At various time points, the altered subnetwork encompassed a combination of unique and overlapping features in terms of metabolic pathways, enzymes, and compounds. For example, certain pathways and enzymes such as the GnRH signaling pathway (at 1h and 21d), Fc gamma R-mediated phagocytosis (at 1h and 21d), linoleic acid metabolism (at 2h and 3h), and lysophospholipase (at 2h and 3h) were implicated in shaping the subnetwork at multiple time points. It is of particular significance that phospholipase A2 (PLA2) and its associated metabolites, such as 1-Acyl-sn-glycero-3-phosphocholine and phosphatidylcholine, were consistently detected in the subnetwork at all time points. Research has indicated that ethanol exposure can reduce the levels of calcium-independent PLA2, an enzyme that facilitates the release of free fatty acids (FFA) and modulates mitochondrial ROS production 37 , 38 . Our study demonstrated a significant down-regulation of phosphatidylcholine and 1-Acyl-sn-glycero-3-phosphocholine at all time points, possibly attributed to an increase in PLA2 activity. This suggested that C-cell mineral water may alleviate symptoms of intoxication by enhancing PLA2 activity, thereby influencing lipid metabolism and reducing oxidative stress associated with alcohol intervention. These findings shed light on the intricate regulatory mechanisms of modulating PLA2 activity in alcohol metabolism. 5. Conclusions This study has demonstrated that the effect of C-cell small cluster mineral water was better than that of Changbaishan water and purified water on relieving drunken in term of extending the latency to drunken, reducing the duration of drunken, reducing serum ethanol levels and stimulating the activities of liver enzymes ADH, ALDH, and CAT. It also up-regulated the expression of genes involved in ethanol metabolism, such as CYP450s , ALDH3B3 , and SULT5A1 , and significantly alterd metabolic pathways including primary bile acid biosynthesis, various drug metabolism pathways, and CYP450-mediated drug metabolism, which could accelerate the conversion of acetaldehyde to acetate, and ultimately metabolize into CO 2 and H 2 O through TCA cycle. These findings will provide innovative strategies for preventing acute alcoholism and relieving chronic alcohol toxicity. Abbreviations Alcohol dehydrogenase (ADH) Aldehyde dehydrogenase (ALDH) Acyl-CoA: ethanol O-acyltransferase (AEAT) Catalase (CAT) Cytochrome P450 (CYP450) Differential genes (DEGs) Ethyl sulfate (EtS) Ethyl glucuronide (EtG) Fatty acids (FAs) Free fatty acids (FFA) Fatty acid ethyl esters (FAEEs) False discovery rate (FDR) Fold change (FC) Kyoto Encyclopedia of Genes and Genomes (KEGG) Metabolite Set Enrichment Analysis (MSEA) Nicotinamide adenosine dinucleotide (NAD) Orthogonal partial least squares discriminant analysis (OPLS-DA) Phosphatidylethanol (PEth) Phospholipase (PLD) Peroxisome proliferator activated receptor alpha (PPAR-α) Principal component analysis (PCA) Quantitative enrichment analysis (QEA) Reactive oxygen species (ROS) Sulfotransferases (SULTs) Tricarboxylic acid cycle (TCA) Uridine diphosphate glucuronyltransferase (UGT) Declarations Author contributions H. Z., Writing-original draft, Methodology, Investigation. H. Q., Software, Methodology, Data curation. M. W., Software, Methodology, Data curation. Y. H., Investigation, Methodology. M. L., Methodology. H. L., Investigation; Methodology. W. S., Methodology, Data curation, Software. C. L., Funding acquisition, Supervision, Writing-review & editing. X. L., Project administration, Funding acquisition, Writing-review & editing. All authors reviewed the manuscript. Conflicts of interest The authors declared that no competing interests exist. Data a vailability The raw sequencing data from the transcriptome sequencing have been archived in the NCBI Short Read Archive database under the Accession Number PRJNA1122326 (The direct link is https://dataview.ncbi.nlm.nih.gov/object/PRJNA1122326?reviewer=qiccrncpq0jsi2b8ud64a38564&page=1). Funding We are very grateful to all participants for their contributions to this study. This work was supported by the National Key Research and Development Program of China (Grant No. 2022YFE0107600, 2022YFC2503300), National Natural Science Foundation of China (Grant No. 81801434, 82220108015), Major Scientific and Technological Innovation Project of the Key Research and Development Program in Shandong Province (Grant No. 2021CXGC011103, 2021ZDSYS06). Declaration of generative AI and AI-assisted technologies in the writing process. During the preparation of this work the authors used the Youdao Translation software in order to edit the language. After using this tool, the authors reviewed and edited the contents as needed and take full responsibility for the contents of the published article. References Sunardi, D. et al. Health effects of alkaline, oxygenated, and demineralized water compared to mineral water among healthy population: a systematic review. Rev. Environ. Health . 39 , 339–349. 10.1515/reveh-2022-0057 (2024). Vitali, M. et al. 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1","display":"","copyAsset":false,"role":"figure","size":788691,"visible":true,"origin":"","legend":"\u003cp\u003eBehavioral indicators and crucial enzymic activities on ethanol metabolism (A) Experimental strategy and flow chart (B) Drunken time (C) Duration of drunken (D) ADH activity (E) ALDH activity (F) Serum ethanol levels (G) CAT activity\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7390244/v1/34255dfa9e26e168f1fe684e.png"},{"id":92093216,"identity":"313fa3cd-2979-43c4-9ba8-3ec2a53ca651","added_by":"auto","created_at":"2025-09-24 14:07:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1799222,"visible":true,"origin":"","legend":"\u003cp\u003eThe characteristics of transcriptomic and metabolomic profiles at 3h post alcohol consumption. (A) The volcano plot of DEGs between t_cell3 with t_con3, which shows up-regulated genes (red, FDR \u0026lt; 0.05 and log\u003csub\u003e2\u003c/sub\u003eFC ≥1), down-regulated genes (green, FDR \u0026lt; 0.05 and log\u003csub\u003e2\u003c/sub\u003eFC ≤1) or no changes (gray). (B) Enriched KEGG pathways based on significantly DEGs between t_cell3 with t_con3. (C) The OPLS-DA with 95% CI of metabolic profiles between m_cell3 and m_con3. (D) The volcano plot of differential metabolites, which shows up-regulated metabolites (red, FDR＜0.05 and FC＞4/3), down-regulated metabolites (blue, FDR＜0.05 and FC＜3/4) or no changes (gray). (E) The heatmap of differential metabolites. (F) KEGG pathway enrichment plot of differential metabolites. (G) Disturbed metabolic sub-network between m_cell3 with m_con3. Red dots represent metabolic pathways, green dots represent compounds, yellow dots represent enzymes, blue dots represent reactions, and green boxes represent input compounds.\u003c/p\u003e\n\u003cp\u003eNote: 1: carbamoyl-phosphate synthase; 2: arginase; 3: ornithine carbamoyltransferase; 4: argininosuccinate synthase; 5: argininosuccinate lyase; 6: amino-acid N-acetyltransferase; 7: 1-acylglycerophosphocholine O-acyltransferase; 8: phosphatidylcholine-sterol O-acyltransferase; 9: albendazole monooxygenase: 10: fenbendazole monooxygenase; 11: pancreatic elastase II; 12: Xaa−Pro aminopeptidase; 13: carboxypeptidase B; 14: carboxypeptidase A2; 15: chymotrypsin; 16: carboxypeptidase A; 17: pancreatic endopeptidase E; 18: glycine hydroxymethyltransferase\u003c/p\u003e\n\u003cp\u003et_con3: control group after 3h at transcriptomic level, t_cell3: C-cell water group after 3h at transcriptomic level; m_con3: control group after 3h at metabolomic level, m_cell3: C-cell water group after 3h at metabolomic level.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-7390244/v1/c2ec7b56875ba7d458ec3fbd.png"},{"id":92092929,"identity":"de5f2b2a-8a8a-42c7-a424-531149f8b977","added_by":"auto","created_at":"2025-09-24 13:59:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":977145,"visible":true,"origin":"","legend":"\u003cp\u003eAlcoholic metabolic activation pathways. (A) Ethanol metabolism pathways in the liver. (B) Comprehensive KEGG analysis of transcriptomics and metabolomics in alcohol metabolism pathway between cell3 with con3. The rectangle represents genes, with red indicating up-regulation and green indicating down-regulation. The dots represent metabolites, with yellow indicating up-regulation and blue indicating down-regulation.\u003c/p\u003e\n\u003cp\u003eNote: ADH: Alcohol dehydrogenase; ALDH: Aldehyde dehydrogenase; CAT: Catalase; FAEE: Fatty acid ethyl esters; FAEES: FAEE synthase; PEth: Phosphatidylethanolfaees, fatty acid ethyl esters; EtS: ethyl sulfate; EtG: ethyl glucuronide; AEAT Acyl-CoA: ethanol O-acyltransferase; PLD Phospholipase; SULT: Sulfotransferase; UGT: Uridine diphosphate glucuronyltransferase.\u003c/p\u003e\n\u003cp\u003econ3: control group after 3h, cell3: C-cell water group after 3h.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-7390244/v1/4b3a5bd5e7a536f8cf8c5f9e.png"},{"id":92095284,"identity":"49dfbb08-9587-4516-b7e6-d82f6b0e165c","added_by":"auto","created_at":"2025-09-24 14:23:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3885040,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7390244/v1/252fc06f-62ff-49db-a373-665221c51ce5.pdf"},{"id":92091798,"identity":"ad08b1d8-eefa-4afa-ae79-a5f0978e7655","added_by":"auto","created_at":"2025-09-24 13:51:57","extension":"rar","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16455526,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.rar","url":"https://assets-eu.researchsquare.com/files/rs-7390244/v1/86d615a8beaf37198aa498ba.rar"},{"id":92092932,"identity":"567b397e-c48a-403b-a997-2d587855c152","added_by":"auto","created_at":"2025-09-24 13:59:56","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1043944,"visible":true,"origin":"","legend":"","description":"","filename":"Graphicabstract.tif","url":"https://assets-eu.researchsquare.com/files/rs-7390244/v1/95b70ea9a6b5d162113c83d9.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"Alcoholic Metabolic Activation in Mice: The Role of A Small Cluster Mineral Water","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eWater is the most abundant component in the human body, comprising a substantial percentage of an individual body weight across different age groups: children (65\u0026ndash;75%), adults (55\u0026ndash;60%), and the elderly (50%)\u003csup\u003e1\u003c/sup\u003e. Many kinds of mineral water available in the market are widely recognized for health benefits. While numerous reports have extolled the virtues of natural mineral water for health\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, there has been little attention given to the specific benefits of small cluster mineral water. C-cell mineral water originates from the mineral-rich Changbai Mountain region in Jilin Province, China. It is naturally weakly alkaline with a pH of 8.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 and contains an array of minerals and trace elements, including lithium, strontium, zinc, and selenium. This makes it a valuable source of essential nutrients for human consumption. What distinguishes C-cell mineral water is its unique small cluster structure, which is achieved through innovative technology. The cutting-edge reactor, composed of nano-scale ion sieve materials derived from silicate crystal minerals, has the capability to alter the dynamic hydrogen bond network system within water cluster groups. This modification weakens or disrupts the hydrogen bonds between water molecules, resulting in the decomposition of large clusters containing 13\u0026ndash;15 water molecules into smaller clusters comprising only 6 water molecules. Through long-range strong magnetic induction facilitated by the reforming reactor, the most stable configuration for hydrogen bonding is achieved with a linear arrangement of six-ringed water molecules\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e (patent number: ZL201410440053.5, ZL201310384523.6). Small cluster water can induce rapid expansion and gradual contraction of cell. Rapid expansion can ensure that there is sufficient water within the cells to maintain the activity of enzymes, substance transport, and normal physiological activities. It also can increase the surface area of cells, enhancing the efficiency of material exchange between cells and the external solution\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Our prior study has demonstrated that consuming C-cell mineral water for 12 weeks improved metabolism and enzyme activity in mice, potentially reducing the risk of obesity\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAlcohol consumption is a prevalent global practice. While moderate intake may offer cardiovascular benefits, chronic and excessive drinking can precipitate a spectrum of health issues, including liver diseases, cardiovascular diseases, dementia, various cancers, and even mortality\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Ethanol, the primary component of alcoholic beverages, is intoxicating but not directly toxic; its metabolites are the culprits behind the associated health risks. Understanding ethanol metabolism is crucial for unraveling the pathophysiological mechanisms of alcohol-related harm\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Ethanol is primarily absorbed in the stomach (22%) and intestine (75%) and is metabolized in the liver into acetaldehyde and acetic acid (~\u0026thinsp;95%)\u003csup\u003e8\u003c/sup\u003e. This metabolic process also leads to an increase in reactive oxygen species (ROS) and a decrease in the NAD\u003csup\u003e+\u003c/sup\u003e/NADH ratio. Ethanol metabolism involves two pathways: oxidation and non-oxidative metabolism. The majority of ethanol (80%-90%) is metabolized to acetaldehyde by cytosolic alcohol dehydrogenase (ADH), leading to the generation of NADH\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The microsomal pathway, involving the cytochrome P450 (CYP) family, accounts for about 10% of ethanol metabolism, with CYP2E1 being a key enzyme. This enzyme converts ethanol into acetaldehyde, producing reactive oxygen species (ROS) that contribute significantly to alcohol's toxicity\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Catalase (CAT), an enzyme found in peroxisomes, also participates in ethanol metabolism, generating ROS and converting ethanol directly into acetaldehyde and water\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The acetaldehyde produced is then oxidized by aldehyde dehydrogenase (ALDH) to form acetic acid\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, a rate-limiting step in alcohol's oxidative metabolism. Acetic acid is further converted into acetyl-CoA, which can enter the tricarboxylic acid cycle or engage in other metabolic processes. The activity of various ADH and ALDH isoforms regulates acetaldehyde concentrations, influencing the risk of alcoholism. The effects of ethanol intolerance, such as nausea, dysphagia, headache, and facial flushing, have been linked to acetaldehyde levels. The accumulation of this metabolite in individuals with inactive or poorly active ALDH isoenzymes may explain cultural aversions to heavy drinking in some societies. Ethanol can also undergo non-oxidative metabolism, with minor pathways converting it into ethyl sulfate (EtS) via sulfotransferases (SULTs), ethyl glucuronide (EtG) through uridine diphosphate (UDP)-glucuronosyltransferase (UGT), fatty acid ethyl esters (FAEEs) by fatty acyl synthases, and phosphatidylethanol (PEth) by replacing choline in phosphatidylcholine (PC)\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;3-A).\u003c/p\u003e\u003cp\u003eAnti-alcoholic drugs may alleviate the symptoms of intoxication but do not address the underlying damage caused by alcohol. Current anti-alcoholic medications encompass chemical medications, traditional Chinese medicine, and health care products containing active ingredients such as peptides, proteins, honey, vitamins, lactic acid protein, and microbial products\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. However, there is no evidence to suggest that natural mineral water could mitigate alcohol-induced harm. This study aims to explore the potential anti-alcoholic effects of C-cell small cluster mineral water in mice.\u003c/p\u003e"},{"header":"2. Animals and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Animals and Experimental Design\u003c/h2\u003e\u003cp\u003eWe procured male C57BL/6J mice, aged 6\u0026ndash;8 weeks with an average body weight of 20\u0026thinsp;\u0026plusmn;\u0026thinsp;2 grams, from Jinan Pengyue Company. Following a one-week acclimatization period, the mice were randomly assigned into four groups based on the intervening measure outlined in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. The intervention included C-cell mineral water (Tasly, Jilin, China), Changbaishan mineral water, RU21, and purified water. The ethanol intervention used Guotai liquor of 53%vol (Guizhou, China). The anti-acute alcohol toxicity experiment within 24h administered twice the above types of drinks at 30 minutes prior to and 5 minutes after the ethanol challenge with a dosage of 13 mL/kg through gavage. The anti-chronic alcohol toxicity experiment extended over 21 days provided with the above types of drinks ad libitum (all day long) and with an alcoholic dosage of 7 mL/kg once a day (Supplementary Material Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The proposed experimental flow chart is outlined below in Fig.\u0026nbsp;1-A. All mice were euthanized by CO\u003csub\u003e2\u003c/sub\u003e. All methods involving experimental animals were performed in accordance with the ARRIVE guidelines and relevant institutional and national regulations, and were approved by the Institutional Animal Care and Use Committee of Qingdao University (Approval No.QDU-AEC-2024689).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Detection of Behavioral Indicators of Drunken\u003c/h2\u003e\u003cp\u003eFour types of drinks including C-cell mineral water, Changbaishan mineral water, RU21, and purified water were given twice to the mice at a dosage of 11 mL/kg, 30 minutes prior to and 5 minutes after the ethanol intervention via gavage. Post ethanol intervention, a subset of 10 mice was randomly selected to monitor behavioral indicators of intoxication, including the drunken latency, duration of drunken over a 24-hour period.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Detection of Serum Ethanol Content\u003c/h2\u003e\u003cp\u003eMice were fed with the above four types of drinks twice at 30 minutes prior to and 5 minutes after the ethanol intervention via gavage, with a dosage of 13 mL/kg. At various time points post ethanol intervention (30, 60, 90, 120, 180, 240, and 300 minutes), serum samples were collected from six mice at each time point. The serum ethanol concentration was promptly measured within 30 minutes using the Ethanol Colorimetric Assay Kit (Elabscience, Wuhan, China).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Activity of ADH、ALDH and CAT in Liver\u003c/h2\u003e\u003cp\u003eThe same intervention was followed as in Section 2.1. After a 120 minutes interval post ethanol intervention, serum samples from six mice at each time point were collected to measure the activities of ADH and ALDH. These enzyme activities were determined using the ADH Activity Assay Kit (Colorimetric) (Abcam, Shanghai, China) and the ALDH Activity Assay Kit (Colorimetric) (Abcam, Shanghai, China), respectively. Following a 21-day chronic alcohol toxicity experiment with a dosage of 7 mL/kg, the activity of CAT was assessed in eight mice per group using the CAT Activity Assay Kit (Elabscience, Wuhan, China).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Liver Transcriptomic Analysis\u003c/h2\u003e\u003cp\u003eLiver tissue samples (25 mg per mouse) were collected from three mice per group (in two groups of C-cell mineral water and Changbaishan mineral water) at 1h, 2h, 3h, and 21d after the alcohol intervention, described as in Section 2.1. Total RNA extracted from the liver was subjected to high-throughput sequencing using the MGISEQ-2000RS platform (Metware, Wuhan, China). Detailed procedures for library preparation, sequencing, and differential analysis are outlined in the Supplementary Material Text S1.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6 Liver Metabolomic Analysis\u003c/h2\u003e\u003cp\u003eTo comprehensively map the metabolic changes, liver tissue samples (25 mg) from each mouse (with six mice per group selected in two groups of C-cell mineral water and Changbaishan mineral water) were analyzed using a modified method from Wu et al., with certain distinctions noted\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. The metabolomic profiling was carried out by UPLC-MS through the services of Metware Biotechnology Co., Ltd. (Wuhan, China). The Supplementary Material Text S2 outlines the detailed methodologies for extraction, identification, and data analysis. Rigorous quality control procedures were implemented to ensure the accuracy and precision of the metabolomic data.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.7 Statistical Analysis\u003c/h2\u003e\u003cp\u003eOne-way and two-way ANOVA followed by Tukey post-hoc testing was conducted to assess statistical significance (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The analysis method of transcriptomic and metabolomic data are presented in the Supplementary Material. For KEGG, we get permission to use the KEGG software from the Kanehisa laboratory\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Behavioral Indicators of Drunken\u003c/h2\u003e\u003cp\u003eOur findings indicated that the latency of drunken for mice in groups of C-cell mineral water and RU21 were significantly extended compared to those in the groups of purified water and Changbaishan mineral water (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;1-B). Additionally, the duration of drunken for the C-cell mineral water and RU21 groups were markedly reduced compared to other drinks groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;1-C) (Supplementary Material Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). These results suggested that the C-cell mineral water group exhibited a significantly superior performance in terms of the drunken latency and the speed of sobering up in terms of duration of drunken compared to the purified and Changbaishan mineral water (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e3.2 Serum Ethanol Levels\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eThe serum alcohol content in C-cell mineral water group was significantly lower than that of in purified water group at 3h and 4h (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;1-F), and serum alcohol level in RU21 group was significantly lower than that of in purified water group at 1h, 1.5h, 2h, 3h and 4h (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;1-F). The results showed that the effect of C-cell mineral water was better than that of purified water on relieving drunken.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e3.3 Activity of ADH、ALDH and CAT\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eTwo hours post alcohol intervention, the activity of the ADH enzyme in the C-cell mineral water group was 1.72 times higher than in the purified water group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;1-D), and the ALDH enzyme activity was 1.29 times higher than in the purified water group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;1-E), indicating a significant enhancement compared to the purified water group. No significant differences were observed at other time points. Upon continuous alcohol intervention over a 21-day period, the CAT activity in the C-cell mineral water group was notably higher than in other groups, suggesting that C-cell mineral water has the potential to enhance CAT enzyme activity (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;1-G).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Transcriptomic Differences\u003c/h2\u003e\u003cp\u003eBy employing transcriptomic analysis with a stringent screening criteria of false discovery rate (FDR)\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |log\u003csub\u003e2\u003c/sub\u003eFold Change| \u0026ge;1, we identified a total of 1462 differential expressed genes (DEGs) across four time points (1 h, 2 h, 3 h, and 21 d). The volcano plots visually depicted these changes, revealing distinct expression patterns between the C-cell mineral water and Changbaishan mineral water group. Specifically, at the 1h mark, 288 genes were up-regulated and 148 genes were down-regulated (Fig \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e-A). At the 2h mark, these numbers were 264 up-regulated and 211 down-regulated (Fig \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e-C). At the 3h point, 182 genes were up-regulated and 170 down-regulated (Fig.\u0026nbsp;2-A). Finally, at the 21d, 89 genes were up-regulated and 110 were down-regulated (Fig \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e-E). Enrichment analysis based on KEGG pathways highlighted several significantly enriched pathways, including metabolic pathways, the PPAR signaling pathway, fatty acid metabolism, inflammatory mediator regulation of TRP channels, and bile secretion (Fig.\u0026nbsp;2-B, Fig \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e-B, S1-D, S1-F). Notably, genes associated with ethanol metabolism, such as \u003cem\u003eCYPs\u003c/em\u003e, \u003cem\u003eALDH3B3\u003c/em\u003e, and \u003cem\u003eSULT5A1\u003c/em\u003e, exhibited significant up-regulation, underscoring their potential roles in the observed physiological responses.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Metabolic Profiling Differences\u003c/h2\u003e\u003cp\u003eWe conducted a comprehensive untargeted metabolomics analysis, discovering a total of 5489 metabolites across both positive and negative ionization modes at the four time points (1h, 2h, 3h, and 21d). Principal component analysis (PCA) was utilized to assess the intrinsic metabolic variations and the quality of the data. The PCA results demonstrated a distinct separation trend between the C-cell mineral water and the Changbaishan mineral water group, suggesting that the metabolic profiles effectively differentiated the two groups at all time points. Additionally, the quality control samples were tightly clustered, attesting to the instrument's repeatability and stability (Fig \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e-A, B, C, D). To gain further insights into the metabolic profiling characteristics, orthogonal partial least squares discriminant analysis (OPLS-DA) was employed. This analysis revealed pronounced separation between the C-cell mineral water group and Changbaishan mineral water group, underscoring the significant metabolic profile differences between the two groups (Fig.\u0026nbsp;2-C, Fig S4-A, Fig S5-A, Fig S6-A). Moreover, the permutation test results, which were repeated 200 times, confirmed that the four OPLS-DA models were well-fitted without any indication of overfitting (Fig \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e-A, B, C, D).\u003c/p\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003ch2\u003e3.5.1 Metabolic Profiling Comparison at 1h Post Intervention Between C-cell and Changbaishan Mineral Water Groups\u003c/h2\u003e\u003cp\u003eA t-test was employed to identify differential metabolites between the two groups, revealing a total of 227 metabolites with FDR \u0026lt;0.05. As depicted in the volcano plot (Fig S4-B) and detailed in Supplementary Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e, the C-cell mineral water group exhibited that 226 metabolites were down-regulation (with FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and Fold change (FC)\u0026lt;3/4), and 1 metabolite was up-regulation (with FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and FC\u0026gt;4/3). All differential metabolites were subsequently subjected to clustering analysis (Fig S4-C). Quantitative Enrichment Analysis (QEA) using global tests uncovered that the predominantly dysregulated metabolic pathways encompassed drug metabolism involving other enzymes, CYP450-mediated drug metabolism, galactose metabolism, glycerolipid metabolism, and sphingolipid metabolism (Fig S4-D). Recognizing that metabolic pathway enrichment analysis might not fully capture the overall, topological, and inter-pathway disruptions, we implemented the Network Propagation-based Algorithm called as FELLA. This advanced algorithm ingested differential metabolites and assessed the impact at each node (metabolites, enzymes, reactions) and each edge (their hierarchical connections) to pinpoint the most significantly perturbed subnetwork. Utilizing this approach, we identified that the interplay among apoptosis, neoptosis, Fc gamma R-mediated phagocytosis, GnRH signaling pathway, and asthma pathways constituted the most significantly affected sub-networks (Fig S4-E).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\u003ch2\u003e3.5.2 Metabolic Profiling Comparison at 2h Post Intervention Between C-cell and Changbaishan Mineral Water Groups\u003c/h2\u003e\u003cp\u003eThe application of t-test analysis discovered 314 differential metabolites with FDR\u0026lt;0.05, distinguishing the two groups. Among these, 2 metabolites were up-regulated (with FC\u0026gt;4/3), while 312 metabolites were down-regulated (with FC\u0026lt;3/4) (Fig S5-B and Table S4). Fig S5-C presented the clustering analysis of these differential metabolites, revealing distinct patterns of metabolic regulation. QEA analysis of the metabolic pathways implicated that the most affected pathways included primary bile acid biosynthesis, the pentose phosphate pathway, glycerophospholipid metabolism, as well as drug metabolism involving other enzymes and the cytochrome P450 pathway (Fig S5-D). Further analysis based on FELLA indicated that the dysregulated metabolic subnetworks were predominantly associated with oxidative phosphorylation, bile secretion, and linoleic acid metabolism, suggesting a complex interplay of metabolic responses perturbations in these groups (Fig S5-E). This analysis provideed a deeper understanding of the metabolic shifts occurring at the 2h mark post intervention, highlighting the divergent effects of C-cell and Changbaishan mineral water on the metabolic profiles.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\u003ch2\u003e3.5.3 Metabolic Profiling Comparison at 3h Post Intervention Between C-cell and Changbaishan Mineral Water Groups\u003c/h2\u003e\u003cp\u003eEmploying t-test analysis based on FC, we identified 210 differential metabolites between the two groups. In comparison to the Changbaishan mineral water group, the C-cell group exhibited 14 up-regulated metabolites and 196 down-regulated metabolites (Fig.\u0026nbsp;2-D and Table S5). A cluster analysis of these metabolites revealed a distinct separation in the heatmap (Fig.\u0026nbsp;2-E). The disturbed metabolic pathways primarily involved steroid biosynthesis, fatty acid degradation, fatty acid elongation, drug metabolism involving other enzymes, cytochrome P450-mediated drug metabolism, caffeine metabolism, and arginine biosynthesis (Fig.\u0026nbsp;2-F). The analysis of disturbed metabolic subnetworks indicated a concentration in arginine biosynthesis and linoleic acid metabolism (Fig.\u0026nbsp;2-G).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\u003ch2\u003e3.5.4 Metabolic Profiling Comparison at 21d Post Intervention Between C-cell and Changbaishan Mineral Water Groups\u003c/h2\u003e\u003cp\u003eThe metabolite volcano plot depicted 103 metabolites with FDR\u0026lt;0.05, with 11 up-regulated and 92 down-regulated (Fig S6-B and Table S6)). In alignment with previous comparisons, a heatmap of significantly differential metabolites showed clear separation between the two groups (Fig S6-C). Enriched metabolic pathways included steroid hormone biosynthesis, sulfur metabolism, sphingolipid metabolism, primary bile acid biosynthesis, drug metabolism involving other enzymes, cytochrome P450-mediated drug metabolism, and cysteine and methionine metabolism (Fig S6-D). The disturbed metabolic subnetworks were predominantly composed of steroid biosynthesis, primary bile acid biosynthesis, lysine degradation, D-amino acid metabolism, Fc gamma R-mediated phagocytosis, and the GnRH signaling pathway (Fig S6-E).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e3.6 Integrated KEGG Pathway Analysis of Metabolome and Transcriptome\u003c/h2\u003e\u003cp\u003eIn order to investigate the impact of C-cell mineral water on alcohol metabolism, a comprehensive KEGG pathway analysis was conducted on the annotated genes and metabolites associated with alcohol metabolism. The results revealed that 64 genes and 5 metabolites were involved in alcohol metabolism. Although some genes and metabolites did not show statistically significant differences, their trends within alcohol metabolism pathways were observable. Specifically, the ALDH gene exhibited an up-regulation trend following the intervention of C-cell mineral water at 1 h, 2 h, and 21 d (Fig S4-F, Fig S5-F, Fig S6-F). Similarly, the \u003cem\u003eCYP2E1\u003c/em\u003e gene showed an up-regulation trend after 2h and 3h of C-cell mineral water intake (Fig S5-F, Fig.\u0026nbsp;2-F). The metabolite NAD\u003csup\u003e+\u003c/sup\u003e consistently showed up-regulation across all four time points (1h, 2h, 3h, and 21d) (Fig S4-F, Fig S5-F, Fig S6-F, Fig.\u0026nbsp;2-F), while NADP\u003csup\u003e+\u003c/sup\u003e was down-regulated at 1h but up-regulated at 21d (Fig S4-F, Fig S6-F). Additionally, pathways such as AMPK signaling and fatty acid biosynthesis were found to be perturbed by the intervention.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIntoxication occurs when a high concentration of alcohol in the bloodstream rapidly reaches the brain, causing it to transition from a state of excitement to inhibition. This shift leads to uncontrolled excitement in the subcortical centers of brain, resulting in a cascade of effects that disrupt cognition, judgment, and motor functions. The most immediate behavioral change is the loss and subsequent recovery of the righting reflex, a key indicator of inebriation. RU21 hangover pill, a popular hangover-relief product with origins in Russia, has made a significant impact on the international market. Its core ingredient is a natural extract, complemented by essential nutrients such as vitamin C, glucose, and glutamic acid. RU21 functions by accelerating alcohol metabolism, specifically by slowing the oxidation of alcohol into the toxic acetaldehyde and facilitating the conversion of acetaldehyde into the less harmful acetate. Its efficacy has been previously reported, and it is commonly used as a positive control in such studies\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. In our investigation of anti-acute alcohol toxicity effects within a 24h window, we compared the hangover-relief effects of different drinks. The C-cell mineral water presented a better anti-hangover effect comparable to that of RU21 (Fig.\u0026nbsp;1). Our findings indicated that the enzymic activities of ADH and ALDH were significantly induced at 2h after alcohol intervention in the group fed with C-cell mineral water, as compared to the purified water group (Fig.\u0026nbsp;1-D, E). Additionally, the serum ethanol concentration at 3h and 4h marks post-intervention was significantly lower in the C-cell mineral water group, suggesting a hangover-relief effect compared with RU21 (Fig.\u0026nbsp;1-F). We hypothesized that C-cell small cluster water may enhance the metabolism of ethanol by boosting the activity of ADH and ALDH, thereby reduced the concentration of acetaldehyde and promote its conversion. Regarding the anti-chronic alcohol toxicity effects, the CAT activity in the C-cell mineral water group was significantly higher than in the control group, indicating that C-cell mineral water offers a degree of protection against chronic alcohol-induced damage. Previous studies conducted by Vitali and Wang have indicated that mineral water has the potential to increase diuresis, aid in the elimination of waste products, prevent urinary stones, and exhibit anti-inflammatory and anti-infective properties\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Our study contributed to the understanding of the potential protective effects of C-cell mineral water against alcohol toxicity, highlighting its ability to mitigate both acute and chronic alcohol-related harm, and emphasizing the need for further research into the role of mineral water components in alcohol metabolism and detoxification.\u003c/p\u003e\u003cp\u003eThe cytochrome P450-mediated drug metabolism pathway was significantly enriched across all four time points (1h, 2h, 3h, and 21d) following C-cell water intervention, as determined by KEGG pathway enrichment analysis of the metabolic profiles, in comparison to the control group. CYP450 enzymes played a crucial role in the metabolism of a wide range of compounds, including drugs, steroids, and vitamins. The connection between human P450s and disease was a subject of considerable interest, particularly the impact of single nucleotide polymorphisms that may result in nonfunctional enzyme variants and contribute to disease pathology\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. CYP2E1, a key enzyme in ethanol metabolism, was of particular interest. In some individuals, a significant portion of CYP2E1 was found in the mitochondria\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. CYP2E1 shared its role in ethanol oxidation with two other enzymes, ADH and CAT\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. CYP2E1 was recognized for its affinity towards small molecules, such as anesthetics\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. It was now understood that several human CYP450s operate primarily through a conformational selection mechanism. Research by Scott and colleagues has shed light on the structural aspects of CYP2E1, with the publication of X-ray crystal structures that revealed the enzymic interactions with both small ligands and larger molecules, such as fatty acids\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. The catalytic mechanism of ethanol oxidation by CYP2E1 involved a series of well-defined steps: substrate binding, reduction of ferric iron to ferrous, binding of molecular oxygen, introduction of a second electron into the iron-oxygen complex, transformation of the complex to Compound I (FeO\u003csup\u003e3+\u003c/sup\u003e), abstraction of a hydrogen atom, oxygen rebound, and finally, product release\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. These insights into the molecular details of CYP2E1 function were invaluable for understanding its role in ethanol metabolism and its potential implications for health and disease.\u003c/p\u003e\u003cp\u003eThe drug metabolism-other enzymes pathway was significantly enriched across all four time points (1h, 2h, 3h, and 21d) following C-cell water intervention, as revealed by KEGG pathway enrichment analysis of the metabolic profiles. This pathway encompassed a variety of metabolic enzymes involved in ethanol metabolism, including alcohol dehydrogenases such as ADH, ALDH, CYP2E1, and CAT, as well as non-oxidative metabolizing enzymes like SULTs, UGTs, and FAEES\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. In the C-cell mineral water group, the transcriptional expression of \u003cem\u003eSULT5A1\u003c/em\u003e was notably up-regulated at 3h after alcohol intervention when compared to the control group. \u003cem\u003eSULTs\u003c/em\u003e facilitated the transfer of a sulfate group from the cofactor 3'-phosphoadenosine 5'-phosphosulfate to substrates containing a hydroxyl (OH) group, playing a pivotal role in the homeostasis of endogenous compounds, which included hormones, neurotransmitters, and bile acids\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eSULTs\u003c/em\u003e constituted a substantial family of enzymes, categorized into six families (\u003cem\u003eSULT1-SULT6\u003c/em\u003e)\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Research has indicated that the gene expression of \u003cem\u003eSULT5A1\u003c/em\u003e was regulated in conjunction with the homeostasis of bile acids in mice subjected to a high-fat diet, with this regulation occurring in an age-dependent manner\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Furthermore, investigations into the processing of drug-metabolizing genes following the pharmacological activation of xeno-sensors, such as 2,3,7,8-tetrachlorodibenzodioxin (TCDD), have demonstrated an increase in the mRNA expression of \u003cem\u003eSULT5A1\u003c/em\u003e. This highlights the potential role of \u003cem\u003eSULT5A1\u003c/em\u003e in the metabolic response to alcohol and its modulation by external stimuli\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFollowing 21d of alcohol treatment, the transcriptional expression of \u003cem\u003eALDH3B3\u003c/em\u003e was found to be up-regulated in the C-cell mineral water group in comparison to the control group. ALDHs are crucial enzymes that catalyze the conversion of toxic aldehydes into harmless carboxylic acids, playing a vital role in detoxification processes. The human genome is known to contain 19 distinct \u003cem\u003eALDH\u003c/em\u003e genes, while the mouse genome harbors 21 \u003cem\u003eALDH\u003c/em\u003e genes\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. The \u003cem\u003eALDH3\u003c/em\u003e family, which includes \u003cem\u003eALDH3A1\u003c/em\u003e, \u003cem\u003eALDH3A2\u003c/em\u003e, \u003cem\u003eALDH3B1\u003c/em\u003e, \u003cem\u003eALDH3B2\u003c/em\u003e, and \u003cem\u003eALDH3B3\u003c/em\u003e, is particularly responsible for the detoxification of lipid-derived aldehydes. Among the various \u003cem\u003eALDH\u003c/em\u003e families, the \u003cem\u003eALDH3\u003c/em\u003e genes exhibit the most significant variation in number across different organisms. Both the mouse and rat ALDH3B3 proteins are classified within the \u003cem\u003eALDH3B2\u003c/em\u003e clade\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. It has been hypothesized that \u003cem\u003eALDH3B2\u003c/em\u003e functions to eliminate lipid-derived aldehydes that accumulate in lipid droplets as a consequence of oxidative stress, thereby serving as a quality control mechanism\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. The up-regulation of \u003cem\u003eALDH3B3\u003c/em\u003e after C-cell mineral water intake suggested a potential enhancement on the body capacity to process and mitigate the toxic effects of lipid-derived aldehydes, which could be particularly beneficial in the context of alcohol metabolism and its associated health implications. This highlighted the importance of further investigating the role of \u003cem\u003eALDH3B3\u003c/em\u003e and the modulation of its expression in alcohol metabolism and detoxification pathways.\u003c/p\u003e\u003cp\u003eThe primary bile acid biosynthesis pathway exhibited significant changes at both the 2h and 21d marks after alcohol intervention in the C-cell mineral water group when compared to the control group. Bile acids (BA), which include both primary and secondary types, are acknowledged as agonists for a variety of receptors. Within the enterohepatic circulation, bile acids have the capacity to enter the systemic circulation, where they can transmit metabolic signals to almost all organs. This is achieved by binding to and activating specialized bile acid receptors, thus modulating the organism physiological metabolic state. It has been documented that ethanol intake can up-regulate the expression of enzymes related to BA synthesis (such as Cyp7a1, Cyp27a1, Cyp8b1, and Baat) and transporters, while concurrently down-regulated the expression of Na\u003csup\u003e+\u003c/sup\u003e-taurocholate cotransporting polypeptides (NTCPs) and the Farnesol X receptor (FXR) in the ileum and liver, respectively\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. This suggested a complex regulatory interplay between ethanol metabolism and bile acid homeostasis. Studies by Brandl et al. have reported significantly elevated levels of total and conjugated BAs in patients diagnosed with alcoholic hepatitis\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. This finding underscored the connection between alcohol-induced liver stress and BA metabolism. Furthermore, researchers have observed that ethanol consumption lead to alterations in intestinal BA metabolism\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, which may have broader implications for gut health and liver function in alcohol consumption. These observations collectively highlighted the intricate relationship between alcohol metabolism and BA regulation, indicating that modulation of BA synthesis and transport may play a crucial role on response to alcohol metabolism and could be a potential target for preventing alcohol induced health problem.\u003c/p\u003e\u003cp\u003eActivation of peroxisome proliferator-activated receptor alpha (PPAR-α) can shift ethanol metabolism from the CYP2E1 pathway, which produced reactive oxygen species (ROS), to the peroxidase pathway, which eliminated ROS, thereby facilitating alcohol elimination\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Our study observed an increase in PPAR-α expression at 2h and 3h after alcohol intervention, indicating that C-cell mineral water may protect against alcohol toxicity by up-regulating the \u003cem\u003ePPAR-α\u003c/em\u003e gene. Additionally, our results suggested that NAD\u003csup\u003e+\u003c/sup\u003e metabolite was up-regulated through the AMPK signaling pathway in the C-cell mineral water group at all time points. Previous research has shown that the PPARα-CAT pathway played a crucial role in regulating NAD\u003csup\u003e+\u003c/sup\u003e synthesis enzymes, maintaining NAD\u003csup\u003e+\u003c/sup\u003e/NADH redox balance, and accelerating alcohol and H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e detoxification in mice\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. We postulated that the potential mechanism of small cluster mineral water is to suppress oxidative stress production, comprehensively enhance alcohol metabolism, and exert a significant anti-alcohol effect. We proposed that the potential mechanism of the small cluster mineral water exerts its effects by suppressing oxidative stress production and comprehensively enhancing alcohol metabolism, thereby exerting a significant protective effect against alcohol-induced damage. This suggested that C-cell mineral water may offer a novel and potentially effective strategy for mitigating alcohol toxicity and promoting metabolic homeostasis.\u003c/p\u003e\u003cp\u003eAs previously discussed, traditional metabolic pathway enrichment analysis may not fully capture the comprehensive, topological, and inter-pathway interactions. To address this limitation, we utilized network propagation-based algorithms to further elucidate the impact of C-cell mineral water on metabolic processes. At various time points, the altered subnetwork encompassed a combination of unique and overlapping features in terms of metabolic pathways, enzymes, and compounds. For example, certain pathways and enzymes such as the GnRH signaling pathway (at 1h and 21d), Fc gamma R-mediated phagocytosis (at 1h and 21d), linoleic acid metabolism (at 2h and 3h), and lysophospholipase (at 2h and 3h) were implicated in shaping the subnetwork at multiple time points. It is of particular significance that phospholipase A2 (PLA2) and its associated metabolites, such as 1-Acyl-sn-glycero-3-phosphocholine and phosphatidylcholine, were consistently detected in the subnetwork at all time points. Research has indicated that ethanol exposure can reduce the levels of calcium-independent PLA2, an enzyme that facilitates the release of free fatty acids (FFA) and modulates mitochondrial ROS production\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Our study demonstrated a significant down-regulation of phosphatidylcholine and 1-Acyl-sn-glycero-3-phosphocholine at all time points, possibly attributed to an increase in PLA2 activity. This suggested that C-cell mineral water may alleviate symptoms of intoxication by enhancing PLA2 activity, thereby influencing lipid metabolism and reducing oxidative stress associated with alcohol intervention. These findings shed light on the intricate regulatory mechanisms of modulating PLA2 activity in alcohol metabolism.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThis study has demonstrated that the effect of C-cell small cluster mineral water was better than that of Changbaishan water and purified water on relieving drunken in term of extending the latency to drunken, reducing the duration of drunken, reducing serum ethanol levels and stimulating the activities of liver enzymes ADH, ALDH, and CAT. It also up-regulated the expression of genes involved in ethanol metabolism, such as \u003cem\u003eCYP450s\u003c/em\u003e, \u003cem\u003eALDH3B3\u003c/em\u003e, and \u003cem\u003eSULT5A1\u003c/em\u003e, and significantly alterd metabolic pathways including primary bile acid biosynthesis, various drug metabolism pathways, and CYP450-mediated drug metabolism, which could accelerate the conversion of acetaldehyde to acetate, and ultimately metabolize into CO\u003csub\u003e2\u003c/sub\u003e and H\u003csub\u003e2\u003c/sub\u003eO through TCA cycle. These findings will provide innovative strategies for preventing acute alcoholism and relieving chronic alcohol toxicity.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAlcohol dehydrogenase (ADH)\u003c/p\u003e\n\u003cp\u003eAldehyde dehydrogenase (ALDH)\u003c/p\u003e\n\u003cp\u003eAcyl-CoA: ethanol O-acyltransferase (AEAT)\u003c/p\u003e\n\u003cp\u003eCatalase (CAT)\u003c/p\u003e\n\u003cp\u003eCytochrome P450 (CYP450)\u003c/p\u003e\n\u003cp\u003eDifferential genes (DEGs)\u003c/p\u003e\n\u003cp\u003eEthyl sulfate (EtS)\u003c/p\u003e\n\u003cp\u003eEthyl glucuronide (EtG)\u003c/p\u003e\n\u003cp\u003eFatty acids (FAs)\u003c/p\u003e\n\u003cp\u003eFree fatty acids (FFA)\u003c/p\u003e\n\u003cp\u003eFatty acid ethyl esters (FAEEs)\u003c/p\u003e\n\u003cp\u003eFalse discovery rate (FDR)\u003c/p\u003e\n\u003cp\u003eFold change (FC)\u003c/p\u003e\n\u003cp\u003eKyoto Encyclopedia of Genes and Genomes (KEGG)\u003c/p\u003e\n\u003cp\u003eMetabolite Set Enrichment Analysis (MSEA)\u003c/p\u003e\n\u003cp\u003eNicotinamide adenosine dinucleotide (NAD)\u003c/p\u003e\n\u003cp\u003eOrthogonal partial least squares discriminant analysis (OPLS-DA)\u003c/p\u003e\n\u003cp\u003ePhosphatidylethanol (PEth)\u003c/p\u003e\n\u003cp\u003ePhospholipase (PLD)\u003c/p\u003e\n\u003cp\u003ePeroxisome proliferator activated receptor alpha (PPAR-\u0026alpha;)\u003c/p\u003e\n\u003cp\u003ePrincipal component analysis (PCA)\u003c/p\u003e\n\u003cp\u003eQuantitative enrichment analysis (QEA)\u003c/p\u003e\n\u003cp\u003eReactive oxygen species (ROS)\u003c/p\u003e\n\u003cp\u003eSulfotransferases (SULTs)\u003c/p\u003e\n\u003cp\u003eTricarboxylic acid cycle (TCA)\u003c/p\u003e\n\u003cp\u003eUridine diphosphate glucuronyltransferase (UGT)\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eH. Z., Writing-original draft, Methodology, Investigation. H. Q., Software, Methodology, Data curation. M. W., Software, Methodology, Data curation. Y. H., Investigation, Methodology. M. L., Methodology. H. L., Investigation; Methodology. W. S., Methodology, Data curation, Software. C. L., Funding acquisition, Supervision, Writing-review \u0026amp; editing. X. L., Project administration, Funding acquisition, Writing-review \u0026amp; editing. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declared that no competing interests exist.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003cstrong\u003evailability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw sequencing data from the transcriptome sequencing have been archived in the NCBI Short Read Archive database under the Accession Number PRJNA1122326 (The direct link is https://dataview.ncbi.nlm.nih.gov/object/PRJNA1122326?reviewer=qiccrncpq0jsi2b8ud64a38564\u0026amp;page=1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are very grateful to all participants for their contributions to this study. This work was supported by the National Key Research and Development Program of China (Grant No. 2022YFE0107600, 2022YFC2503300), National Natural Science Foundation of China (Grant No. 81801434, 82220108015), Major Scientific and Technological Innovation Project of the Key Research and Development Program in Shandong Province (Grant No. 2021CXGC011103, 2021ZDSYS06).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of generative AI and AI-assisted technologies in the writing process.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the preparation of this work the authors used the Youdao Translation software in order to edit the language. After using this tool, the authors reviewed and edited the contents as needed and take full responsibility for the contents of the published article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSunardi, D. et al. 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Neurochem\u003c/em\u003e. \u003cb\u003e131\u003c/b\u003e, 163\u0026ndash;176. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/jnc.12789\u003c/span\u003e\u003cspan address=\"10.1111/jnc.12789\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"alcohol metabolism, small cluster mineral water, alleviation of alcohol toxicity","lastPublishedDoi":"10.21203/rs.3.rs-7390244/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7390244/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo explore the molecular mechanisms underlying the effects of a specific small cluster mineral water (C-cell mineral water) on ethanol metabolism, we conducted a series of assessments comprising anti-acute alcohol toxicity experiments including behavioral hangover responses, serum ethanol levels, liver activities of alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH), along with metabolomic and transcriptomic analyses within 24h, and anti-chronic alcohol toxicity experiments including analysis of liver catalase (CAT) activity, along with metabolomic and transcriptomic profiling after 21d intervention of ethanol accompany with C-cell mineral water. The results suggested that the C-cell mineral water significantly delayed the latency of drunken and decreased the duration of drunken in mice, simultaneously reduced serum ethanol level at 3h and 4h. It also enhanced liver ADH and ALDH activities at 2h and activated CAT activity at 21d, compared to purified water. Transcriptomic analysis revealed that some genes related to ethanol metabolism including \u003cem\u003eCYP450s\u003c/em\u003e, \u003cem\u003eALDH3B3\u003c/em\u003e, and \u003cem\u003eSULT5A1\u003c/em\u003e were up-regulated. Additionally, the metabolomic analysis identified that the most significantly altered pathways included primary bile acid biosynthesis, various drug metabolism pathways, and CYP450-mediated drug metabolism. Subnetworks with maximum changes featured interactions between pathways of oxidative phosphorylation, arginine biosynthesis, and primary bile acid biosynthesis, etc. The results showed that the effect of C-cell mineral water was better than that of purified water on relieving drunken, which could accelerate the conversion of acetaldehyde to acetate, and ultimately metabolize into CO\u003csub\u003e2\u003c/sub\u003e and H\u003csub\u003e2\u003c/sub\u003eO through TCA cycle. These findings will provide innovative strategies for preventing acute alcoholism and relieving chronic alcohol toxicity.\u003c/p\u003e","manuscriptTitle":"Alcoholic Metabolic Activation in Mice: The Role of A Small Cluster Mineral Water","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-24 13:51:51","doi":"10.21203/rs.3.rs-7390244/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-14T06:33:54+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-07T23:11:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-06T11:59:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"206465618005310422746351634223668290463","date":"2025-10-28T21:42:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"23725871975048826424568881911909392585","date":"2025-10-27T12:28:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"211478116200746539376404710888031925038","date":"2025-10-06T14:48:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-26T08:58:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"323447900381063145039112690516756849597","date":"2025-09-16T08:43:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-16T02:55:41+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-16T01:17:50+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-08T11:22:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-05T08:56:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-09-05T08:52:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5e3f29fd-60e9-4b35-aaa8-4d848a8a91e5","owner":[],"postedDate":"September 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":55079372,"name":"Biological sciences/Biochemistry"},{"id":55079373,"name":"Biological sciences/Molecular biology"}],"tags":[],"updatedAt":"2026-01-28T03:53:40+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-24 13:51:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7390244","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7390244","identity":"rs-7390244","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}