Application of epigallocatechin-3-gallate in preparation of acute respiratory distress syndrome product

Abstract

The invention provides an application of epigallocatechin-3-gallate in preparation of an acute respiratory distress syndrome product. The epigallocatechin-3-gallate can be used for treating acute respiratory distress syndrome. According to the application disclosed by the invention, the ARDS induced by lipopolysaccharide is treated by utilizing the epigallocatechin-3-gallate and improving intestinal microorganisms and metabolite short-chain fatty acid, and a new way is opened up for the treatment of the ARDS.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medicine, in particular to a use of epigallocatechin-3-gallate in preparation of an acute respiratory distress syndrome product. BACKGROUND

[0002] Acute Respiratory Distress Syndrome (ARDS) is a severe clinical syndrome characterized by acute progressive refractory hypoxemia, caused by various causes, and the main features include severe inflammatory response, oxidative damage, etc. Many major diseases such as severe pneumonia, Severe Acute Respiratory Syndrome (SARS), COVID-19, severe sepsis and severe pancreatitis can lead to ARDS.

[0003] At present, the treatment methods of ARDS mainly include general supportive treatment and protective mechanical ventilation strategy: the former includes infection control, nutritional support, blood glucose control, stress ulcer prevention and thrombus prevention, etc.; the latter aims to reduce lung damage, including fluid management, low tidal volume ventilation and prone position ventilation. These treatment methods have improved the survival rate of ARDS patients to some extent, but overall, the treatment effect of ARDS has not met expectations, which highlights the problem of lack of effective drug treatment for ARDS patients.

[0004] Therefore, it is urgent to develop an effective drug for treating ARDS. SUMMARY

[0005] The present application provides a use of epigallocatechin-3-gallate in preparation of an acute respiratory distress syndrome product, which solves the problem of lack of effective drug treatment for ARDS patients.

[0006] The pathogenesis of Acute Respiratory Distress Syndrome (ARDS) is complex and not fully understood, and the following two mechanisms are closely related to its pathogenesis: first, inflammation is one of the core mechanisms of ARDS. When the body is stimulated by pathogenic factors (such as lipopolysaccharide, infection, etc.), immune cells will start the antigen clearance process and trigger an inflammatory response. In this process, inflammatory cells secrete a large amount of cytokines or inflammatory mediators, such as TNF-α, IL-1β, IL-6, etc., which in turn trigger a cascade of inflammatory reactions; at the same time, the expression of anti-inflammatory cytokines such as IL-4 and IL-10 is excessively inhibited. This imbalance between pro-inflammatory and anti-inflammatory factors will further exacerbate the inflammatory response, directly leading to lung tissue damage, therefore, drugs that can intervene in the inflammatory response are considered to have the potential to treat ARDS.

[0007] Secondly, oxidative damage is another important mechanism that drives the progression of ARDS. A large number of inflammatory mediators produced during the inflammatory response, combined with the local hypoxic state of the lung, can induce the body to produce excess oxygen free radicals. These oxygen free radicals can react with lipids and proteins on the cell membrane, destroying the structural integrity and functional stability of the cell membrane, leading to increased cell permeability. This damage directly affects alveolar epithelial cells and capillary endothelial cells, causing alveolar hemorrhage, pulmonary edema and hyaline membrane formation, ultimately accelerating the pathological process of ARDS.

[0008] In summary, inflammation and oxidative damage are currently recognized as key pathogenesis mechanisms of ARDS, which provides a core basis for subsequent search for targeted treatment targets.

[0009] The human skin and mucosal surfaces (such as the gastrointestinal tract, respiratory tract mucosa) are colonized with a large number of microorganisms, collectively known as the symbiotic microflora. Among them, the composition of respiratory tract microorganisms is not only affected by the microorganisms in the adjacent parts and the external environment, but also regulated by the microorganisms in the distal parts such as the intestine: this cross-organ interaction between the intestine and the lung is defined as the "gut-lung axis". Under normal physiological conditions, the intestinal flora can maintain a dynamic ecological balance with the host and the external environment, and plays a protective role by strengthening the intestinal barrier and regulating immune function; but when the intestinal flora is imbalanced (such as a decrease in flora diversity and excessive proliferation of harmful bacteria), the integrity of the intestinal barrier is destroyed, the risk of bacterial translocation is significantly increased, and the systemic immune system is activated, promoting bacterial migration to the lungs, and ultimately inducing lung immune damage.

[0010] The relevance of the "gut-lung axis" suggests that by regulating the intestinal flora, it may be possible to intervene in ARDS mediated by inflammatory cascades and oxidative damage. Previous studies have shown that in LPS-induced ARDS model rats, compared with the normal control group, the composition of intestinal microorganisms in the non-intervened model group rats was significantly abnormal; after FMT intervention, the richness, unevenness and diversity of the intestinal flora of the model rats were restored to near normal levels, accompanied by a decrease in pro-inflammatory factor release, an increase in anti-inflammatory factor release, a decrease in oxidative stress, and ultimately a significant improvement in lung damage: this result further verifies the key role of the "gut-lung axis" in the pathogenesis of ARDS, and provides experimental evidence for developing ARDS treatment programs from the perspective of intestinal microecology.

[0011] The technical method of the present application is as follows:

[0012] The present application provides a use of epigallocatechin gallate in the preparation of an acute respiratory distress syndrome product. The epigallocatechin gallate (EGCG) of the present application is the most abundant catechin in green tea, belonging to the flavan-3-ol family of polyphenols, and has eight free hydroxyl groups in its molecular structure, making it one of the most active components in green tea.

[0013] The product of the present application is a product for improving acute respiratory distress syndrome induced by lipopolysaccharide by improving intestinal microorganisms and metabolites SCFAs. Here, improving intestinal microorganisms and metabolites short-chain fatty acids is to increase the abundance of mucinophilic Akkermansia in the intestinal flora. Here, AKK bacteria are mucinophilic Akkermansia.

[0014] Specifically, intestinal flora metabolites are important mediators for intestinal flora to exert physiological functions, and their components are complex, including short-chain fatty acids (SCFAs), amino acids and polypeptides, vitamins, trace elements, etc., among which short-chain fatty acids (produced by intestinal anaerobic bacteria) can directly affect key pathological processes such as inflammatory response and oxidative damage, and become the focus of research. SCFAs can participate in the regulation of body immunity and metabolism through stimulating the growth of symbiotic bacteria, regulating intestinal barrier function, reducing oxidative stress level, inducing local and systemic anti-inflammatory response, etc. The present application shows that supplementing SCFAs to ARDS model rats can significantly improve the condition, confirming that intestinal flora and its metabolites SCFAs play an important role in the occurrence and development of ARDS.

[0015] SCFAs mainly include acetate, propionate, butyrate, isobutyrate, and valerate, among which acetate, propionate, and butyrate account for as high as 90% to 95%, and the ratio of the three is about 3:1:1. Acetate, also known as acetate, is the most abundant component of SCFAs.

[0016] Among them, acetate (also known as acetate): as the most abundant component of SCFAs, it has been confirmed in recent years that it can bind to short-chain fatty acid receptors (G protein-coupled receptor 43, GPR43), reduce intracellular calcium ion concentration, and then promote the ubiquitination of Nod-like receptor protein 3 (NLRP3) inflammasome, and degrade NLRP3 through the autophagy pathway, ultimately reduce NLRP3 inflammasome-related inflammatory response. Animal experiments show that acetate can protect mice from NLRP3 inflammasome-dependent peritonitis and LPS-induced endotoxemia injury, while reducing the levels of pro-inflammatory cytokines and chemotactic factors, inhibiting the phosphorylation of mitogen-activated protein kinase (MAPK) in lung tissue, and reducing LPS-induced ARDS lung injury through anti-inflammatory and antioxidant activities.

[0017] Propionate: Produced by intestinal bacteria such as Bacteroidetes, Firmicutes, and Trichophyton, which break down carbohydrates, propionate possesses anti-inflammatory, antioxidant, and immunomodulatory properties. Studies have confirmed that propionate can inhibit the expression of pro-inflammatory factors such as IL-1β, IL-6, and TNF-α in the intestine, while regulating oxidative damage-related indicators (increasing total antioxidant capacity (T-AOC), total superoxide dismutase (T-SOD), catalase (CAT), and glutathione peroxidase (GSH-px) levels, and decreasing malondialdehyde (MDA) levels). Furthermore, its physiological concentration can rapidly enhance the colonic epithelial barrier function and reduce damage to the intestinal mucosa from harmful substances.

[0018] Butyrate: mainly produced by the breakdown of dietary fiber by intestinal bacteria. Its core functions include providing energy to colon cells, maintaining intestinal wall integrity, and regulating the growth of intestinal flora. It also has a clear anti-inflammatory effect: it can regulate early immune inflammatory response by activating G protein-coupled receptors, regulating signaling pathways such as NF-κB, JAK / STAT, and p38 / ERK-MAPK, as well as the transcription of related genes.

[0019] Therefore, the occurrence and development of ARDS can be intervened by reshaping the gut microbiota structure and regulating the content and composition ratio of key SCFAs such as acetate, propionate, and butyrate.

[0020] The product of this invention inhibits the JAK2 / STAT3 signaling pathway and the SIRT1-PGC1-α signaling pathway. EGCG treatment specifically promotes a significant increase in the abundance of AKK bacteria in the gut microbiota, enhances the production of SCFAs, and transports these microbial metabolites to lung tissue through systemic circulation, thereby regulating the JAK2 / STAT3 signaling pathway in the lungs, reducing the inflammatory response, and thus treating ARDS.

[0021] The product of this invention also improves the intestinal mucosal barrier function. On the one hand, it reshapes the intestinal flora structure (such as reducing the invasion of harmful bacteria into the intestinal mucosa), and on the other hand, it increases the level of SCFAs (especially butyrate, which can enhance the colonic epithelial barrier function), jointly repairing the damaged intestinal mucosal barrier under ARDS, reducing bacterial translocation and endotoxin entry into the blood, thereby indirectly alleviating lung inflammation and oxidative damage, forming a closed loop of "intestinal protection → lung benefit".

[0022] The products of this invention include any one or more of pharmaceuticals, food, and health products.

[0023] The beneficial effects of this invention include:

[0024] I. Innovative Treatment Approach: Acute respiratory distress syndrome (ARDS) is a serious and life-threatening lung disease, and current treatment methods are limited and their effectiveness needs improvement. This invention proposes using epigallocatechin-3-gallate (EGCG) to treat lipopolysaccharide-induced ARDS by improving gut microbiota and short-chain fatty acids in its metabolites, opening up a new avenue for ARDS treatment. Previous ARDS treatments have largely focused on interventions within the lungs themselves, while this invention, starting from the novel perspective of gut microbiota, holds the promise of overcoming the limitations of traditional treatments and providing patients with a more effective treatment option.

[0025] II. Precise Targeted Regulation: A close "gut-lung axis" link exists between the gut microbiota and lung health. Lipopolysaccharide-induced ARDS may be accompanied by an imbalance in the gut microbiota and abnormalities in metabolites such as short-chain fatty acids. EGCG can specifically regulate the composition of the gut microbiota and the production of short-chain fatty acids, such as regulating the levels of short-chain fatty acids like acetate, propionate, butyrate, isobutyrate, and valerate. These short-chain fatty acids can affect the inflammatory response and physiological function of the lungs through multiple mechanisms, such as regulating the activity of immune cells and improving the function of pulmonary vascular endothelial cells, thereby improving ARDS. This precise targeted regulation may improve the effectiveness and safety of treatment.

[0026] III. Advantages of Product Diversity: Meeting Diverse Needs: The products of this invention include any one or more of pharmaceuticals, foods, and health supplements. Pharmaceuticals can provide precise therapeutic dosages and clear therapeutic effects, suitable for the clinical treatment of ARDS patients; foods and health supplements can serve as daily preventative and adjunctive treatment methods, suitable for people with different health conditions and needs. For example, for people with high-risk factors for ARDS, such as long-term smokers or those with chronic lung diseases, consuming foods or health supplements containing EGCG can regulate gut microbiota and improve intestinal mucosal barrier function, reducing the risk of ARDS; for ARDS patients, consuming related foods and health supplements in conjunction with drug treatment may help improve treatment efficacy and promote recovery.

[0027] IV. Improved Accessibility and Adherence: Compared to traditional drug treatments, food and health supplements are more readily accepted by the public, resulting in higher patient adherence. People can easily obtain and consume these products in their daily lives, without the strict adherence to specific dosages and timings required for medication. This makes the technical methods of this invention more practically valuable, enabling better promotion and dissemination, and bringing health benefits to more people. Attached Figure Description

[0028] Figure 1 A graph showing the diversity and salient features of the gut microbiota regulated by EGCG in mice; among which, Figure 1A is a Venn diagram of the gut microbiota composition after EGCG and LPS treatment; Figure 1 B is a graph showing the ACE diversity index among different groups; Figure 1 C represents the Chao diversity index among different groups; Figure 1 D is the graph of observed features among different groups; Figure 1 E is a plot of the Shannon diversity index among different groups; Figure 1 F is a plot of the Simpson diversity index among different groups; Figure 1 G is a graph representing the β-diversity analysis of the gut microbiota of mice in different experimental groups based on principal coordinate analysis (PCoA); where N = 5;

[0029] Figure 2 The EGCG-treated mice exhibit unique gut microbiota composition at the phylum and family levels; among them, Figure 2 Relative abundance diagram of Verrucomicrobia, Actinobacteria, and Bacteroidetes at the A-level; Figure 2 B represents the abundance of the families Trichophyceae, Ruminococciaceae, Spongiaceae, and Verruciformisaceae at the family level;

[0030] Figure 3 EGCG induces mice to possess a unique gut microbiota composition; among which, Figure 3 A is a heatmap analysis diagram of the community at the genus level; Figure 3 B is a community heatmap analysis diagram at the species level; Figure 3 C is the LEfSe analysis plot of the differential abundance taxa detected between different groups after EGCG and LPS treatment; where N=5.

[0031] Figure 4 A diagram showing how EGCG can improve LPS-induced intestinal mucosal damage; among which, Figure 4 A shows the H&E staining results of intestinal tissues from mice in each group (scale bar = 50 μm); Figure 4 B represents the quantitative analysis of intestinal tissue histological scoring; Figure 4 CD was determined by qRT-PCR to detect the levels of ZO- and occludin in mouse intestinal tissue. Figure 4 E represents the protein expression levels of ZO-1 and occludin in the intestinal tissue of mice in each group, as detected by Western blotting. Figure 4 FG represents the determination of the relative protein expression levels of ZO-1 and occludin relative to Tubulin using ImageJ software; Figure 4 H represents the expression levels of ZO-1 and occludin in the intestinal tissue of mice in each group, detected by immunohistochemistry (scale bar = 20 μm). Figure 4IJ represents the mean fluorescence intensity (MFI) of ZO-1 and occludin detected using ImageJ software; all data were normalized with reference to the control group. All data are expressed as mean ± standard error (SEMs). (N=5, compared with the control group: ####p<0.0001, compared with the LPS group: **p<0.01, ***p<0.001, ****p<0.0001);

[0032] Figure 5 The gut microbiota of EGCG-treated mice can alleviate LPS-induced lung injury; among them, Figure 5 A is a schematic diagram of the experimental design for Experiment 2, which uses an antibiotic cocktail therapy (ABX). Figure 5 Protein concentration in B BALF; Figure 5 C-staining with H&E can clearly show the histomorphological features of the lungs (scale bar = 50 μm); Figure 5 D represents the histological score of lung tissue, which can be used for quantitative analysis. Figure 5 EG is a blood cell analyzer used to count cell numbers, including total white blood cell count, neutrophils, and monocytes / macrophages; Figure 5 HQ is a method for measuring serum levels of IL-1β, IL-6, TNF-α, IL-4, IL-10, MDA, CAT, GAPX1, SOD, T-AOC, and other inflammatory and oxidative stress levels using a mouse ELISA kit. Figure 5 RW used a mouse ELISA kit to measure the levels of IL-1β, IL-6, TNF-α, IL-4, IL-10, MDA, and other inflammatory and oxidative stress-related substances in BALF. All data were normalized with reference to the control group. All data are expressed as mean ± standard error (SEMs); (N=5, compared with the control group: ####p<0.0001, compared with the LPS group: ****p<0.0001, compared with the LPS+EGCG (20mg / Kg) group: nsp>0.05).

[0033] Figure 6 The gut microbiota of EGCG-treated mice can alleviate LPS-induced inflammation and oxidative stress; among them, Figure 6 AD used a mouse ELISA kit to measure the levels of oxidative stress, such as CAT, GAPX1, SOD, and T-AOC, in BALF. Figure 6 EO was performed in strict accordance with the operating procedures of the mouse ELISA kit to measure the levels of inflammation and oxidative stress, including IL-1β, IL-6, TNF-α, IL-4, IL-10, ROS, MDA, CAT, GAPX1, SOD, and T-AOC, in lung tissue. Figure 6PT measured the levels of IL-1β, IL-6, and TNF-α, IL-4, and IL-10 inflammatory factors in mouse lung tissue using qRT-PCR. All data were normalized with reference to the control group. All data are expressed as mean ± standard error (SEMs). (N=5, compared with the control group: ####p<0.0001, compared with the LPS group: ****p<0.0001, compared with the LPS+EGCG (20mg / Kg) group: nsp>0.05).

[0034] Figure 7 The image shows that the gut microbiota of EGCG-treated mice can alleviate LPS-induced intestinal mucosal damage; among them, Figure 7 A shows the H&E staining images of the intestinal tissues of mice in each group (scale bar = 50 μm); Figure 7 B represents the quantitative analysis of intestinal tissue histological scoring; Figure 7 CD was determined by qRT-PCR to measure the mRNA levels of ZO-1 and occludin in mouse intestinal tissue. Figure 7 E represents the expression levels of ZO-1 and occludin proteins in the intestinal tissue of mice in each group, detected by immunohistochemistry (scale bar = 20 μm). Figure 7 FG represents the MFI (Method Detection Index) for ZO-1 and occludin proteins detected using ImageJ software; Figure 7 H represents the analysis of β-diversity of gut microbiota in different experimental groups of mice based on principal coordinate analysis (PCoA) (N=5); Figure 7 I. Community heatmap analysis at the species level; Figure 7 LEfSe analysis of differential abundance taxa detected among different groups; all data were normalized with reference to the control group; all data are expressed as mean ± standard error (SEMs). (N=5, compared with the control group: ####p<0.0001, compared with the LPS group: **p<0.01, ***p<0.001, ****p<0.0001, compared with the LPS+EGCG (20mg / Kg) group: nsp>0.05).

[0035] Figure 8 Graphs illustrating how AKK bacteria alleviate LPS-induced lung injury; among which, Figure 8 A is a schematic diagram of the experimental design used in Experiment 3; Figure 8 B represents the protein concentration in BALF; Figure 8 C-staining with H&E can clearly show the histomorphological features of the lungs (scale bar = 50 μm); Figure 8 D represents the histological score of lung tissue, which can be quantitatively analyzed. Figure 8 EG is a cell count performed using a hematology analyzer, including total white blood cells, neutrophils, and monocytes / macrophages.Figure 8 HQ is a method for detecting the levels of inflammatory and oxidative stress substances such as IL-1β, IL-6, TNF-α, IL-4, IL-10, MDA, CAT, GAPX1, SOD, and T-AOC in serum using a mouse ELISA kit. Figure 8 RW (Reference Wing) was performed using a mouse ELISA kit to detect the levels of IL-1β, IL-6, TNF-α, IL-4, IL-10, and MDA in BALF (Basal Body Fluid) to assess inflammation and oxidative stress. All data were normalized with reference to the control group. All data are expressed as mean ± standard error (SEMs); (N=5, compared with the control group: ###p<0.001, ####p<0.0001; compared with the LPS group: **p<0.01, ***p<0.001, ****p<0.0001; compared with the LPS+EGCG (20mg / Kg) group: nsp>0.05).

[0036] Figure 9 A graph depicting the reduction of LPS-induced inflammation and oxidative stress in AKK bacteria; among which, Figure 9 AD was determined by using a mouse ELISA kit to measure the levels of oxidative stress, such as CAT, GAPX1, SOD, and T-AOC, in BALF. Figure 9 EO was performed in strict accordance with the operating procedures of the mouse ELISA kit to measure the levels of inflammation and oxidative stress, including IL-1β, IL-6, TNF-α, IL-4, IL-10, ROS, MDA, CAT, GAPX1, SOD, and T-AOC, in lung tissue. Figure 9 PT was determined by qRT-PCR to measure the levels of IL-1β, IL-6, and inflammatory factors such as TNF-α, IL-4, and IL-10 in mouse lung tissue. All data were normalized with reference to the control group. All data are expressed as mean ± standard error (SEMs). (N=5, compared with the control group: ###p<0.001, ####p<0.0001; compared with the LPS group: **p<0.01, ***p<0.001, ****p<0.0001; compared with the LPS+EGCG (20mg / Kg) group: nsp>0.05).

[0037] Figure 10 A diagram illustrating how AKK bacteria alleviate LPS-induced intestinal mucosal damage; among which, Figure 10 A shows the H&E staining images of the intestinal tissues of mice in each group (scale bar = 50 μm); Figure 10 B represents the quantitative analysis of intestinal tissue histological scoring; Figure 10 CD was performed using qRT-PCR to detect the levels of ZO-1 and occludin in mouse intestinal tissue. Figure 10E represents the expression levels of ZO-1 and occludin proteins in the intestinal tissue of mice in each group, detected by immunohistochemistry (scale bar = 20 μm). Figure 10 FG represents the mean fraction (MFI) of ZO-1 and occludin proteins detected using ImageJ software; all data were normalized with reference to the control group. All data are expressed as mean ± standard error (SEMs); (N=5, compared with the control group: ###p<0.001, ####p<0.0001; compared with the LPS group: *p<0.05, **p<0.01, ***p<0.001; compared with the LPS+EGCG (20mg / Kg) group: nsp>0.05);

[0038] Figure 11 This diagram illustrates how AKK works by increasing SCFA concentrations; where, Figure 11 A represents the metabolite analysis of mice in the LPS+AKK group based on principal component analysis (PCA); Figure 11 B represents the thermographic analysis of fecal metabolites; Figure 11 CE was used to detect the levels of SCFAs in feces, serum, and lung tissue using an ELISA kit for mouse SCFAs; (N=5; compared with the LPS group, *p<0.05, **p<0.01, ****p<0.0001); Figure 11 F represents the difference in abundance of each short-chain fatty acid component in the feces of mice in the LPS+AKK treatment group (N=5; p<0.0001 compared with acetic acid); all data were normalized with reference to the control group. All data are expressed as mean ± standard error (SEMs);

[0039] Figure 12 A diagram showing how SCFAs can alleviate LPS-induced lung injury; among them, Figure 12 A is a schematic diagram of the experimental design used in Experiment 4; Figure 12 B represents the protein concentration in BALF; Figure 12 H&E staining of lung tissue can clearly show the histomorphological characteristics of lung tissue (scale bar = 50 μm); Figure 12 D represents the histological score of lung tissue used for quantitative analysis; Figure 12 EG uses a blood cell counter to count the number of cells, including total white blood cells, neutrophils, and monocytes / macrophages; Figure 12 HQ used a mouse ELISA kit to measure the levels of inflammatory and oxidative stress substances such as IL-1β, IL-6, TNF-α, IL-4, IL-10, MDA, CAT, GAPX1, SOD, and T-AOC in serum; Figure 12RW used a mouse ELISA kit to measure the levels of IL-1β, IL-6, TNF-α, IL-4, IL-10, MDA, and other inflammatory and oxidative stress-related substances in BALF. All data were normalized with reference to the control group. All data are expressed as mean ± standard error (SEMs); (N=5; compared with the control group: ###p<0.001, ####p<0.0001; compared with the LPS group: *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001; compared with the LPS+EGCG (20mg / Kg) group: nsp>0.05);

[0040] Figure 13 A map showing how SCFAs alleviate LPS-induced inflammation and oxidative stress; among which, Figure 13 AD was determined by using a mouse ELISA kit to measure the levels of oxidative stress, such as CAT, GAPX1, SOD, and T-AOC, in BALF. Figure 13 EO was performed in strict accordance with the operating procedures of the mouse ELISA kit to measure the levels of inflammation and oxidative stress, including IL-1β, IL-6, TNF-α, IL-4, IL-10, ROS, MDA, CAT, GAPX1, SOD, and T-AOC, in lung tissue. Figure 13 PT was determined by qRT-PCR to measure the levels of IL-1β, IL-6, and inflammatory factors such as TNF-α, IL-4, and IL-10 in mouse lung tissue. All data were normalized with reference to the control group. All data are expressed as mean ± standard error (SEMs). (N=5; Compared with the control group: ###p<0.001, ####p<0.0001; Compared with the LPS group: *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001; Compared with the LPS+EGCG (20mg / Kg) group: nsp>0.05).

[0041] Figure 14 A diagram illustrating how SCFAs alleviate LPS-induced intestinal mucosal damage; among which, Figure 14 A shows the H&E staining results of intestinal tissues from mice in each group (scale bar = 50 μm); Figure 14 B represents the quantitative analysis of intestinal tissue histological scoring; Figure 14 CD was performed using qRT-PCR to detect the levels of ZO-1 and occludin in mouse intestinal tissue. Figure 14 E represents the expression levels of ZO-1 and occludin proteins in the intestinal tissue of mice in each group, detected by immunohistochemistry (scale bar = 20 μm). Figure 14FG represents the mean fraction (MFI) of ZO-1 and occludin proteins detected using ImageJ software; all data were normalized with reference to the control group. All data are expressed as mean ± standard error (N=5; compared with the control group: #####p<0.0001; compared with the LPS group: *p<0.05, **p<0.01, ***p<0.001; compared with the LPS+EGCG (20mg / Kg) group: nsp>0.05).

[0042] Figure 15 This is a network pharmacology diagram showing the PPI network, MetaScape, and KEGG analysis of the cross-genes between EGCG and ARDS inflammatory damage; among them, Figure 15 A is a Venn diagram of network pharmacology analysis of EGCG and ARDS-related targets; Figure 15 B is a PPI network map constructed from the intersection genes obtained from network pharmacology; Figure 15 CE represents MetaScape enrichment analysis of network pharmacology; (C) biological process (BP) analysis; (D) molecular function (MF) analysis; (E) cellular component (CC) analysis. Figure 15 F represents the KEGG pathway enrichment analysis of cross-genes in network pharmacology;

[0043] Figure 16 This is a diagram showing the PPI network, MetaScape, and KEGG pathway analysis of differentially expressed genes and ARDS-related genes from transcriptomics; among them, Figure 16 A is a Venn diagram of differentially expressed genes and ARDS-related targets in transcriptomics; Figure 16 B is a PPI network map constructed from transcriptomic differentially expressed genes and ARDS intersection genes; Figure 16 CE represents MetaScape enrichment analysis of differentially expressed genes in transcriptomics and genes intersecting with ARDS; (C) biological process (BP) analysis; (D) molecular function (MF) analysis; and (E) cellular component (CC) analysis. Figure 16 F represents the KEGG pathway enrichment analysis of differentially expressed genes and ARDS-intersecting genes in transcriptomics.

[0044] Figure 17 JAK2 / STAT3 is a target map of SCFAs; among them, Figure 17 A represents the detection of protein expression levels of P-JAK2, JAK2, P-STAT3, and STAT3 in the lung tissue of mice in each group by Western blotting. Figure 17 BC refers to the determination of the relative protein expression levels of P-JAK2 / JAK2 and P-STAT3 / STAT3 relative to Tubulin using ImageJ software; Figure 17D represents the expression levels of P-JAK2 and p-STAT3 proteins in the lung tissue of mice in each group, as detected by immunofluorescence assay (scale bar = 20 μm). Figure 17 EF represents the mean fluorescence intensity (MFI) of p-JAK2 and p-STAT3 proteins detected using ImageJ; all data were normalized with reference to the control group; all data are expressed as mean ± standard error (SEMs); (Compared with the control group: ####p<0.0001; Compared with the LPS group: *p<0.05, **p<0.01, ***p<0.001; Compared with the LPS+EGCG (20mg / Kg) group, nsp>0.05);

[0045] Figure 18 The diagram shows the PPI network, MetaScape, and KEGG analysis of EGCG and oxidative stress cross-genes in network pharmacology; among them, Figure 18 A is a Venn diagram of network pharmacology analysis of EGCG and ARDS-related targets; Figure 18 B is a PPI network map constructed from the intersection genes obtained from network pharmacology; Figure 18 CE represents MetaScape enrichment analysis of network pharmacology; (C) biological process (BP) analysis; (D) molecular function (MF) analysis; (E) cellular component (CC) analysis. Figure 18 F represents the KEGG pathway enrichment analysis of cross-genes in network pharmacology;

[0046] Figure 19 This is a diagram showing the PPI network, MetaScape, and KEGG pathway analysis of differentially expressed genes and oxidative stress-crossing genes in transcriptomics; among them, Figure 19 A is a Venn diagram of differentially expressed genes and ARDS-related targets in transcriptomics; Figure 19 B is a PPI network map constructed from transcriptomic differentially expressed genes and ARDS intersection genes; Figure 19 CE represents MetaScape enrichment analysis of differentially expressed genes in transcriptomics and genes intersecting with ARDS; (C) biological process (BP) analysis; (D) molecular function (MF) analysis; and (E) cellular component (CC) analysis. Figure 19 F represents the KEGG pathway enrichment analysis of differentially expressed genes and ARDS-intersecting genes in transcriptomics.

[0047] Figure 20 A diagram showing how SCFAs alleviate LPS-induced oxidative stress in mice by inhibiting the SIRT1 / PGC1-α signaling pathway; among which, Figure 20 A represents the detection of the protein expression levels of SIRT1 and PGC1-α in the lung tissue of mice in each group by Western blotting; Figure 20BC uses ImageJ software to determine the relative protein expression levels of SIRT1 and PGC1-α relative to Tubulin; Figure 20 D represents the protein expression levels of SIRT1 and PGC1-α in the lung tissue of mice in each group, as detected by Western blotting. Figure 20 EF used ImageJ software to determine the relative protein expression levels of SIRT1 and PGC1-α relative to Tubulin; Figure 20 GK uses a mouse ELISA kit to detect the levels of oxidative stress in serum MDA, CAT, GAPX1, SOD, and T-AOC; Figure 20 LP is a mouse ELISA kit used to detect oxidative stress levels in BALF including MDA, CAT, GAPX1, SOD, and T-AOC; Figure 20 The SX assay kit was used to detect the levels of ROS, MDA, CAT, GAPX1, SOD, and T-AOC in lung tissue of mice. All data were normalized with reference to the control group. All data are presented as mean ± standard error (Means ± SEMs); (N=5, compared with the control group: ###p<0.001, ####p<0.0001; compared with the LPS group: *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001; compared with the LPS+EGCG (20mg / Kg) group, nsp>0.05; compared with the LPS+SCFAs group, &p<0.05, &&p<0.01, &&&p<0.001, &&&&p<0.0001). Detailed Implementation

[0048] The present invention will be described in detail below through embodiments and experimental examples. However, these are merely examples and do not limit the present invention in any way.

[0049] In this invention, unless otherwise specified, all raw materials used in the preparation are commercially available products well known to those skilled in the art.

[0050] Example 1: EGCG alleviates LPS-induced ARDS inflammation in mice by improving intestinal mucosal barrier function and remodeling gut microbiota composition.

[0051] This study employed advanced and mature 16S rRNA sequencing technology. The results showed that Venn diagram analysis revealed high statistical and biological similarity in the microbial community composition of the LPS+EGCG group, the LPS group, and the control group, specifically evidenced by significant overlap in their Venn diagrams. However, the LPS+EGCG group exhibited significantly different bacterial communities, which may be key targets for the unique biological effects of EGCG, warranting further investigation into their functions and mechanisms of action. Figure 1 A). α-diversity analysis showed that the EGCG-treated mice exhibited significantly higher α-diversity indices in their gut microbiota compared to the LPS and control groups, including the Chao index, ACE index, observed features, Shannon diversity index, and Simpson diversity index. This result strongly suggests that EGCG effectively promotes the proliferation and diversification of gut microbiota, playing a positive regulatory role in maintaining the stability and balance of the gut microbiota. Figure 1 B to Figure 1 F). Beta diversity analysis based on principal coordinate analysis (PCOA) further revealed differences in gut microbiota composition among different groups. The results showed that the gut microbiota composition of the EGCG-treated group was significantly different from that of the LPS group and the control group (F). Figure 1 G). At different taxonomic levels, the abundance of specific bacterial communities in the EGCG-treated mice showed dynamic changes compared to the LPS-treated and control groups. At the phylum level, the relative abundance of Verrucous, Actinobacteria, and Bacteroidetes was upregulated to some extent. Figure 2 A). Specifically, the phylum Verruciformis participates in various metabolic processes in the intestinal ecosystem, and its increased abundance may indicate optimization of the intestinal microecological environment; the phylum Actinobacteria is closely related to functions such as host immune regulation, and its relative abundance may help maintain immune homeostasis; the phylum Bacteroidetes plays an important role in food digestion and nutrient absorption, and changes in its abundance may affect the nutrient uptake efficiency of mice. At the family level, the abundance of Trichophyceae, Ruminococciaceae, Spongiaceae, and Verruciformisaceae increased ( Figure 2B). These bacterial families have diverse functions in the gut. The families *Trichophyton* and *Ruminococcus* can ferment dietary fiber, producing beneficial metabolites such as short-chain fatty acids, providing energy to the host and regulating intestinal immunity. The ecological functions of the spongy fungi family are relatively complex, and their increased abundance may have unique effects on the structure and function of the gut microbiota. The *Verruciformis* family is closely related to the health of the intestinal mucosa, and its increased abundance may help enhance intestinal barrier function. At the genus level, the abundance of *Verruciformis*, *Ruminococcus*, *Clostridium*, and *Prevotella* showed an increasing trend. Figure 3 A). *Verruciformis* can maintain intestinal homeostasis by regulating the metabolism of the intestinal mucus layer; *Ruminococcus* participates in the degradation and fermentation of polysaccharides; *Clostridium* has multiple metabolic functions in the intestine, and changes in its abundance may affect intestinal metabolism and energy balance; *Prevotella* spp. is associated with the host's health status, and increased abundance may have a positive effect on the intestinal microecological environment. At the species level, the abundance of species such as *Ackermania* also increased significantly. Figure 3 B). Akkermansia is a bacterium closely related to gut health, capable of improving intestinal barrier function, regulating immune responses, and participating in energy metabolism. Linear discriminant effect size (LEfSe) analysis showed that the abundance of Akkermansia in EGCG-treated mice was significantly increased compared to the LPS group and control mice. Figure 3 C). This result further indicates that, compared with the control group and the LPS-treated group, the LPS+EGCG group mice have unique gut microbiota composition characteristics, especially with a significant increase in the abundance of beneficial bacteria such as Akkermania at the phylum, class, genus, and species levels.

[0052] LPS-induced ARDS inflammatory damage impairs the intestinal mucosa. This is mainly manifested in the decreased expression levels of intestinal tight junction proteins, such as occludin-1 (ZO-1) and occludin, thereby disrupting the integrity of the intestinal barrier. Once the intestinal barrier integrity is disrupted, bacteria can migrate into the bloodstream, triggering a systemic inflammatory response. Furthermore, the disruption of intestinal tight junctions is likely a key pathway in the development and progression of LPS-induced ARDS. To clarify the ameliorative effect of EGCG on intestinal barrier function, this invention examined the state of the intestinal mucosa and the expression of intestinal tight junction proteins. Pathological examination of the intestines showed that the LPS group had significant intestinal mucosal swelling, a large number of inflammatory cell infiltrations in the mucosal layer, significant villus separation, and severe intestinal mucosal damage. EGCG intervention effectively improved these pathological changes. Figure 4 A). Regarding pathological scores, the LPS group was significantly higher than other groups, and after EGCG treatment, the pathological scores significantly decreased. Figure 4B). The expression of ZO-1 and occludin was detected using qRT-PCR, Western blotting (WB), and immunohistochemistry. qRT-PCR revealed that, compared with the control group, the mRNA expression levels of ZO-1 and occludin in LPS-treated colon tissue were significantly reduced. However, EGCG pretreatment restored the expression of these two tight junction proteins, with the LPS+EGCG (20 mg / kg) combined treatment group showing a more significant recovery effect. Figure 4 To further validate the results, Western blot and immunohistochemistry were used to detect the expression of ZO-1 and occludin. Highly consistent with the results of qRT-PCR, both Western blot and immunohistochemistry showed that LPS treatment significantly reduced the expression levels of ZO-1 and occludin in colon tissue compared to the control group. EGCG pretreatment effectively reversed this trend, promoting the recovery of expression of both tight junction proteins, and the LPS+EGCG (20 mg / kg) combined treatment group showed a more significant advantage in restoring expression. Figure 4 Our findings suggest that EGCG treatment may affect LPS-induced ARDS by altering the gut microbiota and intestinal barrier function, with Akkermansia myxophilus (AKK) potentially playing a role. This specific alteration of the gut microbiota and stabilization of the intestinal barrier function may be an important biological basis for EGCG's role in combating LPS-induced lung injury.

[0053] Example 2: EGCG treatment of the gut microbiota in mice independently alleviated LPS-induced inflammatory damage in mouse ARDS.

[0054] The 16S rRNA sequencing results showed that the gut microbiota of the LPS+EGCG group mice differed significantly from both the control group and the LPS group at the phylum, family, genus, and species levels. This study conducted a fecal microbiota transplantation (FMT) experiment (Experiment 2) to further analyze the mechanism by which EGCG improves the LPS-induced inflammatory response in mouse ARDS by regulating the gut microbiota and its intrinsic relationship. See the detailed experimental design diagram below. Figure 5 A. The results of Experiment 2 revealed the effects of EGCG fecal microbiota transplantation on LPS-induced ARDS mice at multiple levels. At the protein level: Mice receiving EGCG fecal microbiota transplantation had a significantly lower BALF protein ratio compared to the LPS group, and were at a comparable level to the LPS+EGCG (20 mg / kg) group. Figure 5B). This result suggests that EGCG fecal microbiota transplantation may have a regulatory effect on pathological processes such as protein exudation in the lungs. Lung pathology: H&E staining of lung tissue showed that the pathological damage in the lungs of mice receiving EGCG fecal microbiota transplantation was significantly reduced compared to the LPS group. Specifically, the degree of inflammatory cell swelling was reduced, tissue edema was improved, alveolar hemorrhage was alleviated, the degree of interstitial and alveolar edema was reduced, alveolar structural damage was repaired, inflammatory cell infiltration was reduced, hyaline membrane formation was inhibited, alveolar thickness tended to normalize, and alveolar cell necrosis was reduced. Correspondingly, the lung pathological score also decreased, and the pathological changes and scores in the lungs of this group of mice were highly consistent with those in the LPS+EGCG (20 mg / kg) group. Figure 5 CD). Inflammatory cell level: Compared with the LPS group, the total number of white blood cells, multinucleated cells, and monocytes in mice receiving EGCG fecal microbiota transplantation were significantly reduced, and there was no significant difference compared with the LPS+EGCG (20mg / kg) group. Figure 5 EGCG fecal microbiota transplantation (EGCG) indicates that EGCG fecal microbiota transplantation can effectively inhibit the recruitment and activation of inflammatory cells during inflammation, thereby alleviating the inflammatory response. At the inflammatory cytokine level: ELISA results showed that, compared to the LPS group, the levels of IL-1β, IL-6, TNF-α, IL-4, IL-10, and MDA in the serum, BALF, and lung tissue of mice receiving EGCG fecal microbiota transplantation were significantly lower than those in the LPS group. Simultaneously, ROS in the lung tissue of mice receiving EGCG fecal microbiota transplantation was downregulated compared to the LPS group, while SOD, CAT, GSH-px, and T-AOC were significantly upregulated. There was no significant difference compared to the LPS+EGCG (20 mg / kg) group. Figure 5 HW, Figure 6 AO). Gene-level detection results indicated that mice receiving EGCG fecal microbiota transplantation had downregulated levels of IL-1β, IL-6, and TNF-α in their lung tissue compared to the LPS group, while the levels of anti-inflammatory factors IL-4 and IL-10 were upregulated. Figure 6 This further confirms that EGCG fecal microbiota transplantation can inhibit the activation of inflammatory signaling pathways at the molecular level and reduce the production and release of inflammatory cytokines. At the intestinal injury level: Intestinal H&E staining showed that mice receiving EGCG fecal microbiota transplantation had reduced intestinal mucosal swelling, improved inflammatory cell infiltration in the mucosal layer, and alleviated villus separation compared to the LPS group, indicating reduced intestinal mucosal damage. Their pathological changes and scores were consistent with the LPS+EGCG (20 mg / kg) group. Figure 7 AB). qRT-PCR analysis of intestinal tissue revealed that the mRNA levels of Zo-1 and occludin in the colon of mice receiving EGCG fecal microbiota transplantation returned to normal compared to the LPS group, and there was no significant difference compared to the LPS+EGCG (20 mg / kg) group. Figure 7CD). Immunohistochemical results of intestinal tissue also showed that, compared with the LPS group, the protein levels of Zo-1 and occludin in the colon of mice receiving EGCG fecal microbiota transplantation were restored, and there was no significant difference compared with the LPS+EGCG (20 mg / kg) group. Figure 7 These results indicate that EGCG fecal microbiota transplantation helps maintain the integrity of the intestinal mucosa and intestinal barrier function. Gut microbiota level: 16S rRNA analysis was performed on the gut microbiota of mice that received EGCG fecal microbiota transplantation (EGCG-FMT) and were treated with LPS, as well as mice in the control and LPS groups. β-diversity analysis revealed significant differences in community composition among the different groups. Figure 7 H). Genus / species level analysis and LEfSe analysis showed that LPS+EGCG-FMT mice exhibited unique taxonomic characteristics. Specifically, the abundance of AKK in EGCG-FMT mice was significantly higher than that in the control group and LPS group ( Figure 7 In summary, EGCG-regulated gut microbiota may independently alleviate LPS-induced inflammatory damage in ARDS, and this mechanism may be closely related to AKK enrichment and enhanced intestinal barrier function.

[0055] Example 3: AKK bacteria are a key mediator of the anti-inflammatory effect of EGCG in LPS-induced ARDS mice.

[0056] In this study, Experiments 1 and 2 involved EGCG treatment in mice and fecal microbiota transplantation (FMT) derived from EGCG treatment, respectively. The results clearly showed that the abundance of Akkermansia mucinans was significantly increased in both mice directly treated with EGCG and those receiving FMT derived from EGCG treatment. Given the close relationship between gut microbiota and inflammatory responses and oxidative stress, and the important role of Akkermansia mucinans in maintaining health, based on these significant findings and existing research, we hypothesize that Akkermansia mucinans likely plays a key regulatory role in the process by which EGCG alleviates LPS-induced inflammatory damage and oxidative stress. To verify this hypothesis, we conducted Experiment 3, the detailed experimental design of which is shown in the diagram below. Figure 8 A. The experiment included a control group, an LPS group, an LPS+EGCG (20 mg / kg) group, and an LPS+AKK group. Detailed analysis of the BALF of mice transplanted with AKK bacteria revealed that the protein concentration in the BALF of this group was significantly lower than that of the LPS group, and comparable to that of the LPS+EGCG (20 mg / kg) group. Figure 8B). At the pathological level of the lungs, H&E staining of lung tissue clearly revealed significant differences in the lungs of mice in different treatment groups. The LPS group mice showed severe signs of tissue damage. Inflammatory stimulation triggered a series of pathological changes, including alveolar wall cell proliferation accompanied by interstitial edema, resulting in significant thickening of the alveolar walls. Simultaneously, pulmonary vasodilation and increased blood flow led to severe congestion. Edema was extremely prominent, with significantly reduced alveolar space, severely affecting the lung's gas exchange function. Extensive infiltration of inflammatory cells further exacerbated the degree of tissue damage. In stark contrast, the lung tissue damage in mice transplanted with AKK bacteria was significantly reduced. The alveolar structure remained relatively intact, providing a good structural basis for normal gas exchange. A significant reduction in inflammatory cell infiltration indicated that the inflammatory response was effectively controlled. The lung pathological score also decreased accordingly, and its trends were highly similar to those of the LPS+EGCG (20 mg / kg) group. The pathological changes and scores of the lungs in the two groups of mice were almost identical. Figure 8 CD). In the analysis of inflammatory cell status, the number and activity of inflammatory cells such as neutrophils and monocytes / macrophages were significantly increased in the LPS group. Neutrophils, as early recruited cells in the inflammatory response, showed a significant increase in their number, indicating a strong inflammatory response; monocytes / macrophages have multiple functions such as phagocytosis and antigen presentation, and their increased activity further promoted the development of the inflammatory response. However, after transplantation of *Akermansia mucinosa*, the number and activity of inflammatory cells decreased, and the trend was consistent with that of the LPS+EGCG (20 mg / kg) group. This fully demonstrates that the inflammatory response was suppressed to a certain extent, suggesting that *Akermansia mucinosa* may alleviate the inflammatory response by regulating inflammatory cell function. Figure 8 EG). Inflammatory cytokine levels: ELISA results showed that, compared to the LPS group, the levels of IL-1β, IL-6, TNF-α, IL-4, IL-10, and MDA in the serum, BALF, and lung tissue of mice transplanted with AKK bacteria were significantly lower than those in the LPS group. Simultaneously, ROS in the lung tissue of mice transplanted with AKK bacteria was downregulated compared to the LPS group, while SOD, CAT, GSH-px, and T-AOC were significantly upregulated. There was no significant difference compared to the LPS+EGCG (20 mg / kg) group. Figure 8 HW, Figure 9 AO). Gene-level detection results indicated that mice receiving AKK transplantation had downregulated levels of IL-1β, IL-6, and TNF-α in their lung tissue compared to the LPS group mice, while the levels of anti-inflammatory factors IL-4 and IL-10 were upregulated. Figure 9This clearly demonstrates that the inflammatory response and oxidative stress were effectively regulated, further proving that *AKK* bacteria have a comprehensive and systematic regulatory effect on pulmonary inflammation and oxidative stress. Regarding intestinal damage, intestinal H&E staining showed that, compared with the LPS group, mice transplanted with *AKK* bacteria exhibited reduced intestinal mucosal swelling, improved mucosal inflammatory cell infiltration, and alleviated villus separation, indicating reduced intestinal mucosal damage. Quantitative scoring of intestinal pathological changes revealed no statistically significant difference in intestinal pathological changes and scores between this group and the LPS+EGCG (20 mg / kg) group. Figure 10 (AB), indicating that *Akkermansia mucinosa* has a similar effect to EGCG in alleviating intestinal inflammation. Further analysis of colon-related indicators revealed that qRT-PCR and immunohistochemistry of intestinal tissue showed that, compared with the LPS group, the mRNA and protein levels of Zo-1 and occludin in the colon of mice transplanted with *Akkermansia mucinosa* were significantly restored, and there was no significant difference compared with the LPS+EGCG (20 mg / kg) group. Figure 10 (CG). This indicates that *Akermansia mucinosa* can effectively repair the intestinal barrier function and maintain the integrity of the intestinal mucosa, with effects highly consistent with EGCG. Based on the above experimental results, we can conclude that *AKK* bacteria can independently exert a therapeutic effect, effectively alleviating LPS-induced ARDS inflammatory damage and oxidative stress, and its effect in reducing ARDS inflammation and oxidative stress is highly similar to that of EGCG. These important findings strongly suggest that the mechanism by which EGCG reduces ARDS inflammation and oxidative damage is likely through increasing the abundance of *AKK* bacteria.

[0057] Example 4: EGCG can improve ARDS by regulating AKK-mediated short-chain fatty acid (SCFA) production and through the gut-lung axis regulatory mechanism.

[0058] Previous studies have shown that Akk bacteria, as the dominant bacteria in EGCG-induced ARDS inflammatory damage, play a crucial role. Furthermore, past research has also confirmed that gut microbiota metabolites play a key role in inhibiting the development and progression of ARDS. To investigate the substances that play a key role in Akk bacteria's inhibition of ARDS inflammatory damage, we used metabolomics to analyze the changes in metabolites after treatment. Through β-diversity analysis of metabolomics, we found that the fecal metabolites of mice treated with LPS+Akk bacteria were significantly different from those of the control group and the LPS group. Figure 11 A). Further differential metabolite analysis revealed that the most significantly altered metabolite was SCFA. Figure 11B). ELISA analysis of EGCG-treated mouse feces revealed that EGCG treatment increased the content of SCFAs in mouse feces, with the most significant increase observed in the LPS+EGCG (20 mg / kg) group, consistent with metabolomics analysis results. Figure 11 C). Further ELISA was used to detect the levels of SCFAs in serum and lung tissue. The results showed that, compared with the control group and LPS group, the levels of SCFAs in the serum and lung tissue of mice treated with EGCG increased, with the most significant increase observed in the LPS+EGCG (20 mg / kg) group. Figure 11 DE). This suggests that elevated SCFAs in the feces of mice treated with EGCG can enter the bloodstream and reach lung tissue, thereby inhibiting ARDS inflammatory damage. Since SCFAs contain multiple components, to further clarify their specific composition, we used GC-MS to precisely analyze the content of each component of SCFAs in the feces of LPS+AKK bacteria mice. The analysis results showed that acetic acid, propionic acid, and butyric acid accounted for a very high proportion of SCFAs, reaching 95%-99%, and the ratio of the three was approximately 4:1:1 (…). Figure 11 F). Based on the above findings, we hypothesize that SCFAs are key metabolites by which EGCG improves LPS-induced ARDS through Akk bacteria regulation, with the ratio of acetic acid, propionic acid, and butyric acid being 4:1:1. To verify this hypothesis, we conducted Experiment 4; the detailed experimental design diagram is shown below. Figure 12 A. The results showed that compared with the LPS group, the protein content in the BALF of mice in the LPS+SCFAs group was significantly decreased, but there was no statistically significant difference compared with the LPS+EGCG (20 mg / kg) group. Figure 12 B). Regarding lung pathology, H&E staining of lung tissue showed severe tissue damage in the lungs of mice in the LPS group. Inflammatory stimulation triggered a series of pathological changes, including alveolar parietal cell proliferation and interstitial edema, resulting in significant thickening of the alveolar walls; pulmonary vasodilation and increased blood flow caused severe congestion. Furthermore, significant edema and narrowing of the alveolar cavities severely impaired gas exchange. Extensive infiltration of inflammatory cells in the lung tissue further aggravated the damage. In stark contrast, lung tissue damage was significantly reduced in the LPS+SCFAs group. The alveolar structure remained relatively intact, providing a good foundation for gas exchange. The significantly reduced inflammatory cell infiltration indicated effective control of the inflammatory response. The lung pathology score decreased accordingly, with a trend highly similar to that of the LPS+EGCG (20 mg / kg) group. There was no statistically significant difference in lung pathology characteristics and scores between the two groups. Figure 12CD). In the analysis of inflammatory cell status, the number of inflammatory cells such as neutrophils and monocytes / macrophages was significantly increased and their activity was significantly enhanced in the LPS group. In contrast, the number of inflammatory cells in the LPS+SCFAs group was reduced and their activity was also decreased, and the trend of change was not statistically significant compared with that of the LPS+EGCG (20 mg / kg) group. Figure 12 EG). Inflammatory cytokine levels: ELISA results showed that, compared to the LPS group, the levels of IL-1β, IL-6, TNF-α, IL-4, IL-10, and MDA in the serum, BALF, and lung tissue of mice in the LPS+SCFAs group were significantly lower than those in the LPS group. Simultaneously, ROS in the lung tissue of mice in the LPS+SCFAs group was downregulated compared to the LPS group, while SOD, CAT, GSH-px, and T-AOC were significantly upregulated. There was no significant difference compared to the LPS+EGCG (20 mg / kg) group. Figure 12 HW, Figure 13 AO). Gene-level detection results indicated that LPS+SCFAs mice had downregulated IL-1β, IL-6, and TNF-α levels in lung tissue compared to LPS mice, while anti-inflammatory factors IL-4 and IL-10 levels were upregulated. Figure 13 This clearly demonstrates that the inflammatory response and oxidative stress were effectively regulated, further proving that SCFAs have a comprehensive and systematic regulatory effect on lung inflammation. Regarding intestinal damage, intestinal H&E staining showed that, compared to the LPS group, the LPS+SCFAs group mice exhibited reduced intestinal mucosal swelling, improved mucosal inflammatory cell infiltration, and alleviated villus separation, indicating a certain degree of reduction in overall intestinal mucosal damage. Quantitative scoring of intestinal pathological changes showed no statistically significant difference in intestinal pathological changes and scores compared to the LPS+EGCG (20 mg / kg) group. Figure 14 (AB). To further explore the relevant mechanisms, we conducted an in-depth analysis of colonic tight junction protein-related indicators. Intestinal tissue qRT-PCR and immunohistochemistry showed that, compared with the LPS group, the mRNA and protein levels of Zo-1 and occludin in the colon of mice in the LPS+SCFAs group were significantly restored. Furthermore, there was no significant difference in the mRNA and protein levels of Zo-1 and occludin between this group and the LPS+EGCG (20 mg / kg) group. Figure 14 These findings strongly suggest that the potential mechanism by which EGCG alleviates inflammatory damage in ARDS is likely through the regulation of AKK-mediated SCFAs production and the intervention of the gut-lung axis.

[0059] Example 5: SCFAs alleviate LPS-induced lung and intestinal inflammatory damage in ARDS by targeting the JAK2 / STAT3 signaling pathway.

[0060] To further elucidate the underlying mechanisms by which SCFAs improve inflammatory damage in ARDS, this study comprehensively utilized network pharmacology and transcriptomics techniques to explore the potential mechanisms by which SCFAs improve ARDS inflammatory damage. At the beginning of the study, network pharmacology analysis identified 104 genes directly related to EGCG from the TCMSP and SwissTargetPrediction databases. Simultaneously, by integrating data from the DisGeNET, OMIM, and GeneCards databases, a comprehensive dataset containing 16,374 inflammation-related genes was constructed. Based on this, using Venn diagram analysis, we precisely identified 96 overlapping genes (detailed gene information is shown in Table 1). Figure 15 A). Based on these overlapping genes, we constructed a PPI network using the STRING database and Cytoscape tool. In-depth analysis of this network revealed that key genes in inflammatory signaling pathways, including JAK2, JAK1, STAT2, STAT1, STAT5A, STAT4, STAT5B, STAT3, NFKB2, NFKB1, NFKBIA, NFKBIB, NFKBIL1, NFKBIE, NFKBIZ, MAPK14, MAP2K2, MAP2K1, PIK3CA, HIF1A, GSK3B, GSK3A, and GSKIP, exhibit high connectivity in the ARDS anti-inflammatory signaling pathway. Figure 15 B). This result strongly suggests that these pathways may play a crucial role in the amelioration of ARDS inflammatory damage by SCFAs. To further explore the biological functions of these overlapping genes, we performed enrichment analysis using MetaScape. The results showed that these overlapping genes were significantly associated with 373 biological processes (BP), 47 cellular components (CC), and 120 molecular functions (MF). Figure 15 Finally, through KEGG enrichment analysis, we observed that the JAK / STAT signaling pathway had a significantly higher score. In addition, inflammatory signaling pathways such as NF-κB, MAPK, PI3K / AKT / HIF-α, and Wnt also achieved high scores. Figure 15 F).

[0061] Table 1. Genes of EGCG and ARDS

[0062]

[0063]

[0064] In transcriptomic analysis, we performed differential gene expression analysis between the control group and the LPS group, and between the LPS group and the LPS+EGCG group. Subsequently, we performed Venn diagram analysis on these differentially expressed genes and a comprehensive dataset containing 16,374 inflammation-related genes, successfully identifying 30 overlapping genes (details are shown in Table 2). Figure 16 A). PPI networks were constructed using STRING and Cytoscape tools to analyze these overlapping genes. The results showed that key genes such as JAK1, JAK2, STAT1, STAT2, STAT3, STAT4, STAT5A, STAT5B, NFKB1, NFKB2, NFKBIA, NFKBIB, NFKBIE, NFKBIL1, NFKBIZ, MAP2K1, MAP2K2, MAPK14, PIK3CA, GSK3A, GSK3B, GSKIP, and HIF1A exhibited high connectivity in the ARDS anti-inflammatory signaling pathway. Figure 16 B). Enrichment analysis using MetaScape revealed that the intersecting genes identified by transcriptomics were associated with 169 biological processes (BP), 24 cellular components (CC), and 67 molecular functions (MF). Figure 16 CE). Through KEGG enrichment analysis, we observed significantly higher scores for the JAK / STAT signaling pathway. Furthermore, inflammatory signaling pathways such as NF-κB, MAPK, PI3K / AKT / HIF-α, and Wnt also received high scores. Figure 16 F).

[0065] Table 2

[0066]

[0067]

[0068] To delve deeper into the molecular mechanisms underlying regulatory interactions, this study systematically assessed the protein expression profiles of key effector molecules in these inflammatory pathways. Quantitative analysis using Western blotting revealed that LPS stimulation significantly increased the phosphorylation levels of JAK2 and STAT3, indicating their activation in LPS-induced inflammatory responses. Notably, pretreatment with 20 mg EGCG and SCFAs effectively reversed this effect, significantly reducing the phosphorylation levels of JAK2 and STAT3. Figure 17Further immunofluorescence analysis of lung tissue revealed that LPS stimulation significantly increased the mean fluorescence intensity of JAK2 and STAT3 phosphorylation; while pretreatment with 20 mg of EGCG or SCFAs effectively reduced the mean fluorescence intensity of JAK2 and STAT3 phosphorylation. Figure 17 F). This result suggests that EGCG exerts its anti-inflammatory effect through SCFAs, at least in part by inhibiting the phosphorylation and activation of JAK2 and STAT3.

[0069] Example 6: SCFAs alleviate LPS-induced oxidative stress in ARDS by targeting the SIRT1 / PGC1-α signaling pathway.

[0070] To further elucidate the underlying mechanisms by which SCFAs improve oxidative stress in ARDS, this study continued to utilize network pharmacology and transcriptomics techniques to explore the potential mechanisms by which SCFAs improve oxidative stress in ARDS. At the beginning of the study, network pharmacology analysis identified 104 genes directly related to EGCG from the TCMSP and SwissTargetPrediction databases. Simultaneously, by integrating data from the DisGeNET, OMIM, and GeneCards databases, a comprehensive dataset containing 15,915 oxidative stress-related genes was constructed. Based on this, using Venn diagram analysis, we precisely identified 96 overlapping genes (detailed gene information is shown in Table 3). Figure 18 A). Based on these overlapping genes, we constructed a PPI network using the STRING database and Cytoscape tool. In-depth analysis of this network revealed that key genes in inflammatory and oxidative signaling pathways, including JAK2, JAK1, STAT2, STAT1, STAT5A, STAT4, STAT5B, STAT3, MAPK14, MAP2K1, MAP2K2, PIK3CA, PDK1, Nrf1, Nrf2, Nrf3, HIF1A, PPARGC1A, PPARGC1B, Sirt2, Sirt3, Sirt4, Sirt6, Sirt7, Sirt1, Sirt5, and Keap1, exhibit high connectivity in the ARDS anti-inflammatory signaling pathway. Figure 18 B). To further explore the biological functions of these overlapping genes, we performed enrichment analysis using MetaScape. The results showed that these overlapping genes were significantly associated with 445 biological processes (BP), 445 cellular components (CC), and 127 molecular functions (MF). Figure 18 Finally, through KEGG enrichment analysis, we observed a significantly higher score for the SIRT1 / PGC1-α signaling pathway.Figure 18 F).

[0071] Table 3 Genes associated with EGCG and oxidative stress

[0072]

[0073]

[0074]

[0075] In transcriptomic analysis, we performed differential gene expression analysis between the control group and the LPS group, and between the LPS group and the LPS+EGCG group. Subsequently, we performed Venn diagram analysis on these differentially expressed genes and a comprehensive dataset containing 15,915 inflammation-related genes, successfully identifying 40 overlapping genes (details are shown in Table 4). Figure 19 A). PPI networks were constructed using STRING and Cytoscape tools to analyze these overlapping genes. The results showed that key genes such as STAT2, STAT5A, STAT4, STAT5B, STAT3, STAT1, JAK1, JAK2, NRF2, KEAP1, NRF1, Sirt2, Sirt3, Sirt4, Sirt6, Sirt7, Sirt1, and Sirt5 exhibited high connectivity in the ARDS anti-inflammatory signaling pathway. Figure 19 B). Enrichment analysis using MetaScape revealed that the intersecting genes identified by transcriptomics were associated with 169 biological processes (BP), 24 cellular components (CC), and 67 molecular functions (MF). Figure 19 CE). Through KEGG enrichment analysis, we observed significantly higher scores for the JAK / STAT signaling pathway. Furthermore, inflammatory signaling pathways such as NF-κB, MAPK, PI3K / AKT / HIF-α, and Wnt also received high scores. Figure 19 F).

[0076] Table 4. Transcriptomic differences and genes associated with oxidative stress

[0077]

[0078] To further confirm that EGCG improves oxidative stress through SCFAs via the SIRT1 / PGC1-α signaling pathway, this study conducted a series of experiments. First, the changes in SIRT1 and PGC-1α protein levels in mouse lung tissue after EGCG treatment were detected. Compared with the LPS group, the levels of SIRT1 and PGC-1α proteins in lung tissue were significantly increased after EGCG pretreatment, with the most significant increase observed in the 20 mg / kg EGCG treatment group. Figure 20AC); then, based on Experiment 4, mice were intraperitoneally injected with EX527 (10 mg / Kg) half an hour before tracheal instillation of LPS. Western blotting analysis of pathway-related proteins showed that, compared with the LPS group, the LPS+SCFAs+EX527 group had significantly higher levels of SIRT1 and PGC-1α proteins in lung tissue, and the effect was better than that of the LPS+SCFAs group. Figure 20 DF); Further ELISA was performed on serum, BALF, and lung tissue of mice in the LPS+SCFAs+EX527 group. The results showed that compared with the LPS group, MDA level was increased, ROS level in lung tissue was downregulated, while antioxidant indicators such as SOD, CAT, GSH-px, and T-AOC were significantly upregulated. There was no statistically significant difference in the trend of change compared with the LPS+EGCG (20mg / kg) group, but compared with the LPS+SCFAs group, the former had significantly increased levels of oxidative stress factors and significantly decreased levels of antioxidants. The differences were statistically significant, indicating that adding EX527 to the LPS+SCFAs treatment can further enhance the expression of oxidative stress factors and aggravate oxidative stress response compared with SCFAs alone. Figure 20 Based on the above results, it can be concluded that EGCG can regulate the SIRT1 / PGC-1α signaling pathway by modulating SCFAs, thereby exerting a comprehensive and systematic regulatory effect on oxidative stress.

[0079] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. Use of epigallocatechin-3-gallate in the preparation of products for acute respiratory distress syndrome.

2. The use according to claim 1, characterized in that, The product is designed to improve lipopolysaccharide-induced acute respiratory distress syndrome by improving gut microbiota and short-chain fatty acids in metabolites.

3. The use according to claim 2, characterized in that, The short-chain fatty acids include one or more of acetate, propionate, butyrate, isobutyrate, and valerate.

4. The use according to claim 2, characterized in that, The improvement of gut microbiota and metabolites, including short-chain fatty acids, is achieved by increasing the abundance of Akkermansia myxophilus in the gut microbiota.

5. The use according to claim 2, characterized in that, The product inhibits the JAK2 / STAT3 signaling pathway and the SIRT1-PGC1-α signaling pathway.

6. The use according to claim 1, characterized in that, The product is also a product that improves the intestinal mucosal barrier function.

7. The use according to claim 1, characterized in that, The products include any one or more of pharmaceuticals, food, and health products.

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