We found that 59 overlapping targets based on component-and AECOPD-related targets were frequently involved in the advanced glycation end product–receptor for advanced glycation end product signaling pathway in diabetic complications, the phosphatidylinositol-3-kinase–protein kinase B signaling pathway, and the hypoxia-inducible factor 1 signaling pathway, which might play important roles in the anti-inflammatory mechanism of TRQ in AECOPD treatment. Moreover, TRQ groups exerted protective effects against AECOPD by reducing the infiltration of inflammatory cells. Meanwhile, TRQ-M and TRQ-H groups significantly downregulated or upregulated the expression of tumor necrosis factor, interleukin (IL) 6, C-reactive protein, IL10, and serum amyloid A, as key targets in network pharmacology, in the serum and bronchoalveolar lavage fluid to achieve anti-inflammatory efficacy. Our study showed that TRQ had better anti-inflammatory efficacy against AECOPD, and initially elucidated its molecular mechanism. Moreover, our study also provides a new strategy to explore effective mechanism of TRQ against AECOPD; and further studies are needed to validate the biological processes and pathways of TRQ against AECOPD.Acute-exacerbation chronic obstructive pulmonary disease (AECOPD) is mainly associated with acute respiratory tract infection. In recent years, a growing number of studies have found that Tanreqing capsule (TRQ) has a favorable anti-inflammatory effect. In this study, we used network pharmacology and pharmacodynamics to explore the molecular mechanism and effects of TRQ in AECOPD treatment. To further understand the molecular mechanism of TRQ in AECOPD treatment, we used the network pharmacology to predict components of TRQ, TRQ-related targets, AECOPD-related targets, and pathways. In addition, we used the cigarette-smoke/lipopolysaccharide -induced AECOPD experimental model in Sprague–Dawley rats (72 rats randomly divided into six groups [ On the basis of clinical and pathological characteristics, COPD is divided into stable COPD and acute-exacerbation COPD (AECOPD). AECOPD is manifested as acute worsening of COPD, which has decreased quality of life and increased mortality2. AECOPD is caused by various pathogenic factors inside and outside of the lungs, including acute respiratory tract infection, pollutants, cold weather and irritants3, and characterized by airway inflammation and mucus hypersecretion4. The inflammatory response may induce parenchymal tissue destruction, resulting in emphysema, and disruption of normal repair and defense mechanisms, and small-airway fibrosis2. AECOPD is mainly treated by reducing inflammation, such as Tanreqing Injection5 and glucocorticoid6.Chronic obstructive pulmonary disease (COPD) is characterized by persistent respiratory symptoms and airflow limitation due to airway and/or alveolar abnormalitiesScutellaria baicalensis Georgi), Bear Bile Powder , Cornu Caprae Hicus , Lonicerae japonicae flos , and Forsythiae fructus  Vahl), and is accordant with formulation of Tanreqing Injection for treating syndromes including fever, cough and expectoration. The relevant studies showed that Tanreqing Injection has been successful applied into the treatment of AECOPD patients. Liu et al. indicated Tanreqing Injection possesses potent exhibitory effects in LPS-induced airway inflammation by suppressing the MAPKS and NF-κB signaling pathways to downregulate the TNF-α, IL1β, IL6 and IL8 levels in BALF and serum, which attenuate the airway inflammation, airway damage, and mucus hypersecretion7. And the previous study indicated that Tanreqing Injection down-regulates the levels of IL-8 and neutrophil elastase (NE) to inhibit the airway inflammation and mucus hypersecretion with satisfactory clinical efficacy in the AECOPD treatment4, and reduces the level of inflammatory factors to improve arterial oxygen partial pressure of AECOPD patients8. In addition, modern pharmacological studies have revealed that TRQ has anti-inflammation, immunomodulation, antibiosis and antivirals9. Fan et al. indicated that TRQ has a good clinical effect on acute bronchitis (cough of wind -heat invading the lung), and shows no toxic and side effects10. And, TRQ significantly decreased the transforming growth factor (TGF) β1, IL6 and CRP expression to improve lung function and inhibit inflammatory response against radiation pneumonitis11. Therefore, we predicted that TRQ was effective on treating AECOPD, few studies have systematically investigated the molecular mechanism and efficacy of TRQ in AECOPD treatment. In order to confirm this prediction, we investigated the effect and anti-inflammatory molecular mechanism of TRQ on AECOPD rats.Tanreqing capsule (TRQ) (Z20130025), a widely used classical compound herbal recipe, consists of Scutellariae radix . The biological network-based framework for understanding the mechanism of Chinese herbal formular has been established for the first time in 2007, and the first international standard of network pharmacology, Network Pharmacology Evaluation Method Guidance, has been formulated in 2021TRQ was supplied by Shanghai Kaibao Pharmaceutical Company Ltd. . Dexamethasone pieces were purchased from Zhejiang Xianju Pharmaceutical Company Ltd. . Whole value grain feed stuff was purchased from SPF (Beijing) Biotechnology Company Ltd. (SCXK (Jing) 2019-0010). Lipopolysaccharide (LPS) (batch: L2880) was obtained from Sigma-Aldrich Company Ltd. Klebsiella pneumoniae  was obtained from National Center for medical Culture Collections . An enzyme linked immunosorbent assay (ELISA) kit used to determine the levels of IL6, IL10 and TNF-α was from Wuhan BOSTER Biological Technology Company Ltd. The levels of SAA and CRP were quantified using the ELISA kit from Elabscience Company Ltd. Paraformaldehyde was from Tianjing Chemical Reagent Company Ltd. Ultra-pure water was prepared with a Milli-Q water purification system .http://tcmspw.com/). Due to the complexity and variety of components, Oral bioavailability (OB) combined with drug likeness (DL) property evaluation were applied to screen the active substance of TCM16. OB ≥ 30% and DL ≥ 0.18 were set as screening thresholds to collect the components17. The constituents of two animal drugs, including BBP and CCH, were selected from the literature21. Targets corresponding to the components were derived from the Swiss Target Prediction database (http://www.swisstargetprediction.ch/) combined with the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). The organism was chosen as “Homo sapiens,” and 1357 targets of components were obtained. AECOPD associated targets were gathered from the GeneCard database (https://www.genecards.org/) and the Online Mendelian Inheritance in Man (OMIM) database (https://omim.org/), which were searched using the keywords “acute-exacerbation of chronic obstructive pulmonary disease”.Bioactive compounds of three herbs in TRQ  were collected from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database (http://www.bioinformatics.com.cn/) , was used to analyze Gene ontology (GO), including biological processes (BP), cellular components (CC), and molecular functions (MF), and the Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment24 of 59 overlapping targets. The targets- pathways map was plotted by http://www.bioinformatics.com.cn, an online platform for data analysis and visualization.A total of 2034 associated targets of AECOPD were gathered, and we found 139 AECOPD targets with a median score of ≥ 38.25. To find 59 targets of TRQ treatment for AECOPD from Venny obtained using the Bioinformatics analysis platform (n/) Fig. , which whttp://www.rcsb.org/), being powerful new tools for exploring 3D macromolecular structures. The above proteins were put into Python software to remove the effect of water and add hydrogen atoms. Finally, molecular docking established by Autodock Tools software was used to validate the network pharmacology results in vitro, moreover, the molecular docking results were visualized by Discovery Studio software.To further predict the interaction of key components and targets of TRQ treatment for AECOPD, the structures of components were collected from the PubChem database and the proteins of targets downloaded from the RCSB PDB : control, model, low-TRQ (TRQ-L), medium-TRQ (TRQ-M), high-TRQ (TRQ-H), and dexamethasone (Dex).Sprague–Dawley rats  (NO.: 1107261911004350), specific-pathogen-free grade, were purchased from the Animal Experimental Center of Shandong . The experimental protocol was reviewed and approved by the Experimental Animal Care and Ethics Committee of the First Affiliated Hospital, Henan University of Chinese Medicine  2015–0005). Animal studies were conducted in accordance with the Animal Research: Reporting of in Vivo Experiments (ARRIVE) guidelines26. Then, the rats aged 1–8 weeks, received nasal instillation of a Klebsiella pneumoniae (KP) suspension (6 × 108 CFU) per week for up to 60 days. Finally, the model, TRQ-L, TRQ-M, TRQ-H, and Dex groups were administrated LPS by intratracheal instillation (2 mg/kg) to induce AECOPD on the first day of the thirteenth week. The KP and LPS doses were selected as previously described27. And control group was kept in polypropylene cages with free access to water and normal chow.Commercially available, filtered Hong Qiqu cigarettes ) were used in the early stage of establishing the AECOPD model. The model, TRQ-L, TRQ-M, TRQ-H, and Dex groups were exposed to cigarette smoke with 3000 ± 500 ppm for 3 h each time, twice a day, for 12 weeks–4 g/kg; formula: Dose (rat) = Dose (human)*6.3 *0.5/1/2 = (2.25 mg/d)/60 kg*6.3*1 = 2.3 × 10–4 g/kg/d) for 7 days. And control and model groups were intragastrically administrated ultra-pure water (10 mL/kg/d) for the same amount of time. Food was prohibited for 12 h prior to the experiment while water was given freely. Blood was collected from the caudal vein and infrarenal aorta. The serum was separated for further analysis.The TRQ-L, TRQ-M, and TRQ-H groups were administrated low-, medium-, and high-TRQ doses, respectively, by intragastric administration  = Dose (human)*6.3*0.5/1/2 = (3.6 g/d)/60 kg*6.3*0.5/1/2 = 0.19/0.38/0.76 g/kg/d) for 7 days  count, the neutrophil cell ratio (NEU%), the lymphocyte ratio (LYM%), and the monocyte ratio (MONO%).The rats were anesthetized by intraperitoneal injection of 10% urethane (1.0 mL/100 g), and tracheal intubation was performed to measure the forced vital capacity (FVC), forced expiratory volume at 100 ms (FEV0.1), forced expiratory volume at 300 ms (FEV0.3), peak expiratory flow (PEF), maximum mid-expiratory flow (MMEF), and functional residual capacity (FRC) to assess changes in the lung function of AECOPD rats before and after TRQ treatment.On the basis of previous studies and combined with PPI analysis, C-reactive protein (CRP), serum amyloid A (SAA), interleukin (IL)6, IL10, and TNF-α selected as biomarkers were quantified to evaluate the therapeutic effects of TRQ in AECOPD treatment. Blood samples collected from the infrarenal aortic were stewed for 2 h and centrifuged at 12,000 rpm for 15 min, and the supernatant was collected to determine the expression levels of CRP, SAA, IL6, and IL10 using the enzyme-linked immunosorbent assay (ELISA) kit according to the manufacturer’s instructions.The left lung was pumped back and forth gently three times to collect the bronchoalveolar lavage fluid (BALF). The BALF was centrifuged at 12,000 rpm for 15 min, and the TNF-α levels in the supernatant were quantified using the ELISA kit according to the manufacturer’s instructions.The left lung tissue was harvested. Samples were fixed in 4% paraformaldehyde, dehydrated, paraffin-embedded, into 4 μm sections, and then stained with hematoxylin and eosin (H&E). The wall thickness (Wt), mean linear intercept (MLI), and mean alveolar number (MAN) were calculated to determine the pathological changes by light microscopy. The schematic diagram of measuring bronchoalveolar wall thickness was that three long-diameters including c1, c2 and c3 and short-diameters including d1, d2 and d3 across the middle of bronchoalveolar were measured under 400blens, the formular of calculating wall thickness(μm) = [(c1−d1) + (c2−d2) + (c3−d3)]/(3 × 2)), as shown in Fig. Statistical analysis was carried out by one-way analysis of variance using SPSS Statistics 26.0. Least significant difference analysis was applied to groups that conformed to the homogeneity test of variance, while Dunnett’s T3 test was performed for groups inconsistent with the homogeneity test of variance. All data were expressed as the mean ± standard deviation, and α < 0.05 was considered statistically significant.21. The components of CCH were similar to those of Saiga tatarica Linnaeus, containing phospholipids, polypeptides, and amino acids19. Nonetheless, we found that only nine components of CCH had 135 potential targets. We collected 35, 23, and 22 components from SR, FF, and LJF according to screening conditions. The relevant targets of 90 components, in which luteolin, quercetin, kaempferol, wogonin, flavanone, and stigmasterol were shared by 2 or 3 herbs, obtained 1357 results. For example, luteolin was shared by LJF and FF. The component information of herbs is described in Table 12. And the network included 156 nodes  and 1351 edges. The mean degree value (the number of target associated with it) of components was 12.46, which indicated that components regulated multiple targets to achieve therapeutic effects. Specially, five compounds, including wogonin, baicalein, 4’-methoxy-7-hydroxyisoflavone, neobaicalein, and β-sitosterol, which acted on 41, 30, 27, 27, and 25 targets, respectively, become the crucial active compounds for the TRQ due to their important positions in this network.Network pharmacology was used to predict TRQ components and overlapping targets, and to obtain GOBP, GOCC, GOMF, and related signaling pathways, which provided direction to further study the molecular mechanism of TRQ. BBP and CCH are constituents of animal drugs, and the components were not retrieved from the TCMSP database. We found that nine components of BBP had 371 potential targetsWe found 59 overlapping targets to construct a PPI network Fig. B. The avP-value in Fig. The number of GOBP, GOCC, and GOMF was 1253, 76, and 44, respectively. GOBP, GOCC, and GOMF with all the top 10 of P-values were screened and were represented by a graphical bar with the Finally, we found 140 related signaling pathways. The top 20 of P-values were represented by a graphical bubble in Fig. Figure We drew 3D interaction diagrams of key targets and their corresponding best-matched components to visualize the molecular docking results Fig. Ca–c. ComP < 0.05), and LYM% dramatically decreased (P < 0.05). And compared with the model group, WBCs in the TRQ groups and Dex group decreased with no statistical significance, NEU% significantly decreased in TRQ-M, TRQ-H groups and Dex goup (P < 0.05 and P < 0.01), LYM% was upregulated in TRQ-M and TRQ-H groups (P < 0.05) and in TRQ-L and Dex groups with therapeutic effect, and MONO% decreased in TRQ groups and Dex group without statistical significance, as represented in Fig. Systemic inhalation of cigarette smoke and KP combined with LPS induced AECOPD. Compared to control group, NEU% of rats in the AECOPD model significantly increased (P < 0.05 and P < 0.01)   Fig. Ba; FEV0.01) Fig. Bc,e. TRQP < 0.05) and was downregulated in TRQ groups with therapeutic effect, as shown in Fig. P < 0.01). Moreover, compared with the model group, IL6 level was significantly downregulated in TRQ-M and TRQ-H and Dex groups (P < 0.05 and P < 0.01), as shown in Fig. SAA, CRP, IL6, and TNF-α were upregulated, while IL10 was downregulated in the model group compared with the control group, indicating successful modeling of AECOPD. The levels of CRP and TNF-α were downregulated in TRQ groups and Dex group, with no significant differences compared with the model group , as indicated in Fig. Compared with the control group, MLI increased, MAN decreased, and airway wall thickness increased in the model group 36. Therefore, the above components might act on 59 overlapping targets to regulate inflammatory-related pathways.Network pharmacology can illustrate the complex interactions among the biological systems, drugs, and disease from a network perspective, which provides new research ideas and technical means to study the mechanisms of action of CM formulae37. Following activation, PI3Ks, members of the intracellular lipid enzyme family, phosphorylate phosphatidylinositol 4,5- bisphosphate (PIP2), producing phosphatidylinositol 3,4,5-trisphos-phate (PIP3), which recruits AKT into the plasma membrane38. The PI3K-AKT signaling pathway is interconnected with several downstream inflammatory, oxidative stress, and apoptotic mediators; therefore, identifying novel multitarget components to attenuate PI3K/AKT regulates related downstream inflammatory cytokines39. The links between hypoxia signaling and inflammation are bidirectional, and hypoxia may exacerbate inflammation through activation of inflammatory pathways and affect immune cell fate and function. The HIF-1 signaling pathway intercepts with inflammation, Notch signaling, and stem cell auto renewal and can be activated in normoxia in response to inflammatory stimuli40. The results investigated that TRQ regulates inflammatory-related pathways to improve and treat AECOPD.In addition, some targets among 59 overlapping targets are highly enriched inflammatory-related pathways, including AGE-RAGE, PI3K-AKT and HIF-1 signaling pathways. The PI3K-AKT signaling pathway plays a critical role in different cellular processes, including metabolism, inflammation, cell survival, motility, and even cancerMolecular docking is an indispensable means to screen active components and calculate the binding affinity of a component to a target, which determines the binding stability. Generally, the lower the affinity, the more stable the binding. Results of molecular docking indicated that AKT1, SAA, TNF, CRP, IL6, IL10 and VEGAF, had significant affinity with the above core components, especially 4’-methoxy-7-hydroxyisoflavone in BBP in our study. Therefore, the above core components could be the pharmacodynamics substances in TRQ that affect the expression of the key targets to treat AECOPD. We initially explored the anti-inflammatory mechanism of TRQ against AECOPD based on network pharmacology, the AECOPD experimental model was used to evaluate the therapeutic potential of TRQ and to verify the network pharmacology in the pharmacological experiment section.41. Quantifying the above cytokines is the current diagnosis and prognosis method for AECOPD. Therefore, the local expression of SAA, CRP, IL6, TNF-α, and IL10 is critical for infiltration of inflammatory cells during AECOPD progression. CRP and SAA levels are the most common indicators used to assess systemic inflammation and curative effects3, which shows similar variation tendencies that SAA expression rising 1000 times in 24 h is the same as CRP39. Some studies have found that the relative SAA expression is significantly higher in the serum of AECOPD patients compared with stable COPD patients and is positively correlated with and regulated by IL642. SAA and IL6 significantly increase during AECOPD, which effectively predicts the AECOPD process43. In addition, some clinical studies also have shown that TNF-α affecting the complex disease process, is higher in AECOPD compared with stable COPD44; and IL10 resolves cigarette-smoke-induced inflammatory responses45. Moreover, Previous studies indicated that the inhibition of SAA, CRP, IL6 and TNF-α could attenuate AECOPD41.AECOPD is mainly associated with aggravated airway inflammation in previous studies, such as increased levels of acute inflammatory, including SAA, CRP, IL6, IL10, and TNF-αIn our research, the AECOPD model in rat, SAA, CRP, IL6 in serum and TNF-α in BALF were significantly upregulated compared with control group. TRQ treatment down-regulated expression of SAA, CRP and IL6 in serum, and TNF-α in BALF. And TRQ treatment, especially TRQ-M and TRQ-H, down-regulated expression of SAA, CRP, IL6, TNF-α. Moreover, the value of IL10, as an anti-inflammatory cytokine, in TRQ-H and TRQ-M was significantly higher than model group, which might imply that TRQ-H and TRQ-M had greater anti-inflammatory capability. In addition, blood cells status in AECOPD model, including the numbers of WBC, NEU% and MONO%, were markedly elevated. The above-mentioned indexes were also improved in the treated groups at different levels. Therefore, our study proved that TRQ improved lung function and decreased systemic inflammation and provided evidence of anti-inflammatory role of TRQ at multiple levels. In our histopathological study, marked inflammatory cell infiltration, alveolar ectasia and fusion, and bronchiolar stenosis were observed in AECOPD rats and were improved in the treated groups at different levels. A high dose of TRQ and dexamethasone has significantly protective effects on the structure of alveoli and airway walls. In addition, the protective effects of high and medium doses of TRQ in alleviating infiltration of inflammatory cells in alveolar spaces and regulating the expression of inflammatory cytokines in AECOPD treatment are better than those of a low dose of TRQ.Taken together, we demonstrated and proved that TRQ exhibits protective effects on alleviating infiltration of inflammatory cells in alveolar spaces and regulating the expression of SAA, CRP, IL6, IL10, and TNF-α in AECOPD treatment. These findings provided the powerful experimental evidences for the network pharmacology predictions. However, our study initially elucidated its molecular mechanism based on network pharmacology integrating molecular docking and pharmacodynamics, and further studies are needed to validate the biological processes and pathways of TRQ against AECOPD.In this study, on the basis of network pharmacology, we systematically revealed molecular mechanism that TRQ can effectively improve the AECOPD-induced inflammatory response. Network pharmacology result preliminarily indicate that TRQ can be used for treating AECOPD by regulating the core targets, including SAA, CRP, IL6, IL10 and TNF-α and relevant signaling pathways , which lays a foundation for the specific molecular mechanism of TRQ against AECOPD. After analysis and verification by experiment, we experimentally validated that TRQ was effective for the treatment of AECOPD by alleviating infiltration of inflammatory cells in alveolar spaces and regulating the expression of inflammatory cytokines in AECOPD treatment.Supplementary Information.


Background: Hepatocellular carcinoma (HCC) is one of the fifty most common cancers globally, having a high mortality rate being the second most common cause of cancer-related deaths. However, little attention has been paid to the involvement of exosomes and ceRNA in HCC.Method: The study aimed to explore exosome data from exoRBase database and a free online database to estimate possible binding miRNA from mRNA, lncRNA, and circRNA and discover useful exosome biomarkers for HCC therapy.Results: The results indicated that a total of 159 mRNAs, 60 lncRNAs, and 13 circRNAs were differentially expressed, with HIST2H3C exhibiting the highest log2FC change, CTD-2031P19 exhibiting the most relevant lncRNA, and CTD-2031P19 exhibiting the most relevant lncRNA. MARCH8, SH3PXD2A, has-circ-0014088, hsa-miR-186-5p, and hsa-miR-613 were identified as hub biomarkers used by Cytoscape. According to the KEGG pathway analysis results, the differentially expressed proteins were primarily enriched in the MAPK signaling network, central carbon metabolism in cancer, the glucagon signaling pathway, glutamatergic synapse, and spliceosome. Furthermore, immunohistochemical images from the Human Protein Atlas (HPA) online tool were used to directly evaluate the protein expression of SMARCA5, CDC42, and UBC between normal and cancer tissues, and the results showed that these three gene expressions were significantly higher in tumor tissues.Conclusion: This study discovered atypical signature exosomes for HCC prognostic prediction based on an online database. The signals could mimic exosome microenvironmental disorders providing potential biomarkers for exosome treatment. Hepatocellular carcinoma (HCC) is one of the fifty most common cancers globally, having a high mortality rate being the second most common cause of cancer-related deaths, and is diagnosed at a rate of 500,000 patients each year globally . The mosBAK1 expression is driven by exosome circ-0051443 via competitive interaction with miR-331-3p and acts as a predictor of HCC and a possible therapeutic target  (The exoRBase (ase.org)  is an onvia the ENCORI platform.By evaluating the expression profiles of the 32 cancer types included in the TCGA study, the ENCORI pan-cancer analysis platform seeks to decode the pan-cancer network of lncRNA, miRNA, pseudogenes, snoRNA, RNA binding protein (RBP), and all protein-coding genes. TargetScan identifies miRNA biological targets by searching for conserved 8mer, 7mer, and 6mer sequences that match the seed region of each miRNA . The miRp-values to FDR values. The R (version 3.5.3) and R Bioconductor software packages analyzed all data, while Perl was used for creating data matrixes and performing all the data processing on p < 0.05.Cytoscape (version 3.7.1) is a bioinformatics software used for constructing and visualizing networks of molecular interactions . CytoscaHIST2H3C exhibiting the highest log2FC change and CTD-2031P19 exhibiting the most relevant lncRNA. 2FC value.After standardizing the microarray results, primarily, the mRNAs, lncRNAs, and circRNAs were selected, which are differentially expressed between normal and HCC samples. The results indicated that a total of 159 mRNAs, 60 lncRNAs, and 13 circRNAs were differentially expressed, with MARCH8, SH3PXD2A, has-circ-0014088, hsa-miR-186-5p, and hsa-miR-613 were identified as hub biomarkers with degrees ≥10. The OS analysis revealed no statistically significant difference in survival for MARCH8 and SH3PXD2A, where a high expression of HIST2H3C indicated poor survival  of 366 HCC patients  survival analysis module. The statistical difference between the curves was assessed using the log-rank test   . The genThe DAVID online database was used to investigate the network’s mRNAs’ functional annotation information and signaling pathways. The results of the GO analysis revealed that changes in biological processes (BP) of differentially expressed proteins were enriched in protein phosphorylation, osteoblast differentiation, positive transcription regulation, DNA-templated, and nucleosome assembly. Histone binding and protein kinase activity were the most affected by changes in molecular function (MF). The most abundant cell components (CC) were the cytoplasm, nucleoplasm, and cytosol. According to the KEGG pathway analysis results, the differentially expressed proteins were primarily enriched in the MAPK signaling network, central carbon metabolism in cancer, the glucagon signaling pathway, glutamatergic synapse, and spliceosome .Tumor-related exosomes or tumor-derived exosomes are considered critical for controlling carcinogenesis and its development. Identifying and analyzing tumor exosomes can help with early diagnosis, efficacy evaluation, and prognosis analysis of cancers, which are envisaged to significantly advance the oncology research, cancer clinical diagnosis, and introduce novel opportunities for cancer treatment. Some novel and effective exosome biomarkers were identified in this study based on online databases, indicating that the signature has great predictive value. The findings of this study may also represent the exosome status of individuals with liver cancer and prospective biomarkers and therapeutic targets in exosome signaling pathways.RGPD6, CTD-2031P19.4, and has-circ-0001380, respectively. Microduplication of RGPD6 was earlier reported in a family with liver cirrhosis and other diseases  is one of the 11 members of the MARCH family of RING-finger E3 ubiquitin ligase. Research reports claim that MARCH8 is an effective antiviral protein that targets viral envelope glycoproteins and reduces their incorporation into the viral particles , MHC II expression, and graft-versus-host disease severity was confirmed (SH3PXD2A-AS1 knockdown decreased colorectal cancer cell proliferation, migration, and invasion in vitro and suppressed carcinogenesis in vivo (SH3PXD2A, a gene encoding Tks5, plays a crucial role in invasion, body formation and function, cell migration, and matrix destruction (via the Wnt/-catenin pathway (This study used a complete exosome analysis using the exoRBase database on normal and HCC samples; 159 differentially expressed mRNAs, 60 differentially expressed lncRNAs, and 13 differentially expressed circRNAs were identified. The most meaningful mRNAs, lncRNAs, and circRNAs were diseases . Targetspatients . There warticles . The immonfirmed . Accordi in vivo . SH3PXD2truction . The SH3 pathway . Accordi pathway . The HOX pathway ; hence,  pathway . The miR pathway , whereas pathway . The RMR pathway . There h pathway . The his pathway . This stBEX2 gene and suppress the activation of the MAPK/JNK signaling pathway, thereby preventing the development of HCC (via inactivating the MAPK/p38 signaling pathway (Mycobacterium tuberculosis. However, the signatures predict that exosomes must be validated in multiple independent cohorts. Though this study provided more information, however, there were some limitations, where the findings have not been validated in clinical samples due to lack of clinicopathologic data, the function of clinical variables in exosomes not being investigated, and the number of genes investigated being insufficient to generalize the importance of exosome transcript upregulation and downregulation in HCC.The functional annotation information and signaling pathways of the mRNAs in the network were then investigated. According to the KEGG pathway analysis results, the differentially expressed mRNAs were primarily abundant in the MAPK signaling pathway, central carbon metabolism in cancer, the glucagon signaling pathway, glutamatergic synapse, and spliceosome. The Ras/MAPK pathway is activated in 50–100% of human HCC; thus, it is linked to a poor prognosis . miR-370t of HCC . Similar pathway . As a re pathway . The enz pathway . This reThis study discovered atypical signature exosomes for HCC prognostic prediction based on an online database. The signals could mimic exosome microenvironmental disorders providing potential biomarkers for exosome treatment. Future research work is certain to undertake large-scale related research, which will eventually be translated into developing new methods for accurate cancer medicine.


P < 0.05). Light microscope observation shows that HJJPD could control the degree of lipid denaturation of the mouse liver tissue to a great extent. RT-qPCR results show that the mRNA expression levels of peroxisome proliferative activated receptor gamma (PPARG), tumor necrosis factor-α (TNF-α), antiserine/threonine protein kinase 1 (AKT1), and prostaglandin-endoperoxide synthase (PTGS2) in the liver tissues of the three HJJPD groups  were significantly lower than those in the model group (P < 0.05). HJJPD can exert its effect by inhibiting hepatic steatosis and related mRNA expression and decreasing the levels of other liver-related indexes. This study suggested that HJJPD exerted its effect on NAFLD by modulating multitargets with multicompounds through multipathways. It also demonstrated that the network pharmacology-based approach might provide insights for understanding the interrelationship between complex diseases and interventions of HJJPD.This paper was designed to predict the mechanisms of the active components of Huaji Jianpi Decoction (HJJPD) against nonalcoholic fatty liver disease (NAFLD) based on network pharmacology-combined animal experiments. The candidate compounds of HJJPD and its relative targets were obtained from TCMSP and PharmMapper web server, and the intersection genes for NAFLD were discerned using OMIM, GeneCards, and DisGeNET. Then, the target protein-protein interaction (PPI) and component-target-pathway networks were constructed. Moreover, gene function annotation (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to study the potential signaling pathways associated with HJJPD's effect on NAFLD. Molecular docking simulation was preformed to validate the binding affinity between potential core components and key targets. Eventually, the candidate targets, the possible pathway, and the mechanism of HJJPD were predicted by the network pharmacology-based strategy, followed by experimental validation in the NAFLD mice model treated with HJJPD. A total of 55 candidate compounds and 36 corresponding genes were identified from HJJPD that are associated with activity against NAFLD, and then the network of them was constructed. Inflammatory response and lipid metabolism-related signaling pathways were identified as the critical signaling pathways mediating the therapeutic effect of the active bioactive ingredients on NAFLD. Compared with the model group, the liver wet weight, liver/body ratio, the levels of total cholesterol (TC), triglyceride (TG), aspartate aminotransferase (AST), alanine aminotransferase (ALT), and high-density lipoprotein (HDL) in serum in the HJJPD low-dose (17.52 g/kg·d), medium-dose (35.04 g/kg·d), and high-dose (70.07 g/kg·d) groups significantly decreased ( With the globalization of obesity and relative metabolic disorders, excess nutrition leads to the prevalence of nonalcoholic fatty liver disease (NAFLD) worldwide . There aTraditional Chinese medicine (TCM) has been widely applied for the regulation of the physiological function of the human body with the advantage of holistic concept and differentiation treatment , 8. ManyAtractylodes macrocephala (Baizhu), Astragalus memeranaceus (Fisch.) Bge. Var. Mongholicus (Bge.) Hsiao (Huangqi), Pinellia ternata (Thunb.) Breit. (Banxia), Citrus reticulata Blanco (Chenpi), Wolfiporia cocos (F. A. Wolf) Ryvarden & Gilb. (Fuling), Coix lacryma-jobi L. var mayuen (ROman.) Stapf (Yiyi Ren), Atractylodes Lancea (Thunb.) DC. (Cangzhu), Citrus aurantium L. (Zhishi), Alisma plantago-aquatica Linn. (Zexie), Ligusticum chuanxiong hort (Chuanxiong), and Nelumbo nucifera Gaertn (Heye) [G. uralensis, C. pinnatifida, and C. reticulata, as the anti-inflammatory and lipid-lowering drug, have remarkable effect in the treatment of liver diseases and NAFLD [C.pinnatifida was a common therapeutic drug that was added in the TCM prescription for the treatment of NAFLD and liver cirrhosis. Hence, HJJPD may be the superior therapeutic strategy for NAFLD according to TCM experience and scientific research. Presently, the molecular mechanisms underlying the efficacy of HJJPD remain uncertain. It is quite meaningful to further study the chemical composition and pharmacology of HJJPD for the treatment of NAFLD.Network pharmacology is a thriving interdisciplinary technology that is related to Chinese traditional medicine, chemical informatics, computer science, and bioinformatics, and it is an efficient and powerful tool for studying the bioactive ingredients and mechanism of Chinese traditional medicine. Huaji Jianpi Decoction (HJJPD), as a folk prescription, was derived from the famous TCM prescription of Zhizhu pill, Liujunzi Detection, and Jiaosanxian, composed of n (Heye) . As per n (Heye) . The maind NAFLD . EspeciaHJJPDs are composed of a variety of TCMs, and they are characterized by multiple components, targets, and pathways, which is of great difficulty for studying the chemical composition and mechanism of HJJPDs . Network80 SPF male C57BL/6N mice aged 3 weeks and weighing 20 ± 2.0 g were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd.  and treated in accordance with the Guide for the Care and Use of Laboratory Animals. The experimental site is the third level scientific research laboratory of traditional Chinese medicine pharmacology, College of Traditional Chinese Medicine, Hebei University (No : TCM-09-315). All animal experiments were reviewed and approved by the Animal Care and Use Committee of Renmin Hospital of Hebei University (IACUC-2018043).Atractylodes macrocephala (Baizhu), Astragalus memeranaceus (Fisch.) Bge. Var. Mongholicus (Bge.) Hsiao (Huangqi), Pinellia ternata (Thunb.) Breit. (Banxia), Citrus reticulata Blanco (Chenpi), Wolfiporia cocos (F.A. Wolf) Ryvarden & Gilb. (Fuling), Coix lacryma-jobi L.var.mayuen (ROman.) Stapf (Yiyi Ren), Atractylodes Lancea (Thunb.) DC. (Cangzhu), Citrus aurantium L. (Zhishi), Alisma plantago-aquatica Linn. (Zexie), Ligusticum chuanxiong hort (Chuanxiong), and Nelumbo nucifera Gaertn (Heye) were obtained from Hebei Anguo medicine market  and identified by Professor Keli Chen of Hubei University of Chinese Medicine. All herbals met the requirements of the Chinese Pharmacopoeia (2020 edition), which have been preserved in the College of Traditional Chinese Medicine, Hebei University (No: TCM-09-315).Trizol reagent kit, total RNA extraction reagent, and DNA marker were purchased from Aidelai Biotechnology Co., Ltd. . HJJPD consisted of Baizhu (30 g), Huangqi (30 g), Banxia (10 g), Chenpi (10 g), Fuling (30 g), Yiyi Ren (30 g), Cangzhu (15 g), Zhishi (15 g), Zexie (10 g), Chuanxiong (10 g), and Heye (10 g). The above medicinal materials are fully mixed and then made into a powder sample using a plant powder extractor . The sample was extracted thrice using traditional Chinese medicine extractor  for 1 h. Following extraction, the samples were centrifuged at 5000 g for 15 min at 25°C using a type centrifuge  to obtain the extracts, which were concentrated using a vacuum rotary evaporator  at 40°C, and the above concentrated extracts were freeze-dried by vacuum freeze dryer , yielding 20.4 g of water extract.http://www.gene2newdrug.com/) and Traditional Chinese Medicine System Pharmacology database and Analysis Platform  on the basis of the rule of five . Meanwhile, the main compounds of herbs were also retained, which has been extensively studied by reported pieces of research [http://www.swissadme.ch/), and target proteins (probability > 0.1) were selected. The target genes for NAFLD were collected from Gene Cards database (https://www.genecards.org/).The active compounds of HJJPD and protein targets of the collected active compounds were obtained from Integrative Pharmacology-based Research Platform of Traditional Chinese Medicine , and the collected target genes and active components were obtained for subsequent network analysis as visualized using Cytoscape 3.7.2 software. Cytoscape software  was applied to visualize the relationship between active compounds and diseases of NAFLD. The core active ingredients were identified in the treatment of NAFLD. The candidate genes were imported into the STRING database (https://string.db.org/) for the construction of PPI network, and the visual networks were established by Cytoscape software . The key genes were selected according to the degree value.The target genes related to NAFLD and active components of HJJPD were obtained by the online Venn map platform (http://metascape.org/gp/index.html). The bubble map of GO and KEGG enrichment results was established using R Studio. The visualization and integration of enrichment results were carried out using Enrichlot and ggplot2 R package. The above steps were completed by R software 3.6.2.The functional annotation of GO and KEGG pathways, including the relevant biological processes (BP), cellular components (CC), molecular functions (MF), and signal pathways of potential anti-NAFLD targets, were performed using the Metascape platform (∗mol format and target protein in ∗PDB format were obtained from software Chem office. According to Homo sapiens and refinement resolution (1.0∼2.0 Å), the target proteins in ∗PDB format were selected from the RSCB PDB database (https://www.rcsb.org/). Then, the ligands and water molecules in the target protein were removed using software Pymol 2.5, and then it was stored in ∗pdbqt format. Lastly, Autodock Vina software was used for molecular docking between active compounds and target proteins [A molecular docking simulation was conducted to assess the binding energy of the core compounds with the key targets. Autodock Vina 1.5.6 software developed by Olson's research group in Scripps Research Institute was adopted to assess molecular docking . Top 10 proteins , 17. TheThe mice in the normal and model groups  were fed normal and high-fat diet, respectively. After 10 weeks, 50 obese mice were randomly divided into 5 groups, including the model group, positive control group, and low-, medium-, and high-dose HJJPD-treated groups. The positive control group was given 0.005 g/mL obeticholic acid by gavage for 6 weeks, and normal saline was given to the control group. Low-, medium-, and high-dose HJJPD-treated groups were given 17.52 g/kg·d, 35.04 g/kg·d, and 70.07 g/kg·d of HJJPD, respectively. Meanwhile, the body weight was recorded at 0, 4, 8, 12, 16, 20, and 24 weeks.All blood samples were collected from the mice orbit after an overnight fast at 24 weeks, and they were centrifuged  to collect the supernatant for subsequent experiments. Mice were sacrificed and dissected. Then, the liver tissues were collected and measured for the liver index and subsequent histological analysis. The liver index (g/g) was calculated usingAspartate aminotransferase (AST), alanine aminotransferase (ALT), the total cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) were analyzed by HITACHI 7600 automatic biochemical analyzer .3 pieces on ice, fixed in 2.5% glutaraldehyde solution for 2 h, washed with 0.1 M PBS for 3 times, fixed with 1% osmium acid for 1 h, washed with 0.1 M PBS for 3 times, dehydrated with alcohol  and acetone gradient, and subjected to Epon812 penetration. Semithin sections (0.5–2 nm) were performed on the embedded mass of liver tissue, and toluidine blue staining was performed. Morphological changes of liver in mice were observed under the optical microscope.The liver tissues were dissected and taken, cut into 1 mmα, AKT1, and PTGS2) were analyzed by RT-qPCR. The RNA extraction of the liver tissue was performed according to the operation guidance in the kit instructions. The nucleic acid protein analyzer detects the quality and concentration of total RNA. The A260/A280 ratio is approximately 2.0, and the RNA content is calculated by test kit. 2.0 μg of total RNA was taken and cDNA was synthesized by reverse transcription  was applied for comparisons among three groups, and post hoc analyses were carried out with the Newman–Keuls multiple comparison test. Statistical significance was considered at P < 0.05 .All experiments were repeated at least three times, and the experimental results are shown as the mean ± SD. Student's b, poricoic acid a, alisol a monoacetate, kumatakenin, baicalin, etc. Table S1 shows the material basis of HJJPD. 4 compounds were overlapped across different herbs, including (+)-Eudesma-4 (15), 7 (11)-Dien-8-One in Baizhu and Cangzhu, 3-O-trans ferulylquinic acid in Chenpi and Chuanxiong, and Nobiletin, Tangeretin in Chenpi and Fuling. The top 10 compounds by the degree value  with chemical structures, molecular weight (Mw), the number of hydrogen bond donors, hydrogen bond acceptors, rotatable bonds, and lipid-water partition coefficient are as shown in HJJPD consists of Baizhu (30 g), Huangqi (30 g), Banxia (10 g), Chenpi (10 g), Fuling (30 g), Yiyi Ren (30 g), Cangzhu (15 g), Zhishi (15 g), Zexie (10 g), Chuanxiong (10 g), and Heye (10 g). HJJPD was extracted using traditional Chinese medicine extractor, and the yield of the extract was 17%. NAFLD, as the most common comorbidity, was the attractive research target for TCM. Baizhu, Fuling, and Huangqin had been reported as the potential TCM for improving NAFLD . AccordiNAFLD was searched as the key word in the Genecard database . ConsequP < 0.05). P < 0.05). The GO functional and KEGG enrichment analyses were performed to study the crucial biological processes of HJJPD in the treatment of NAFLD. As per the GO analysis results, 36 genes were enriched in 508 GO entries that consisted of 2401 biological progress (BP), 9 cellular components (CC), and 25 molecular functions (MF) (β (Table S3), PPARG, PTGS2, ESR1, LPL, PPARA, and HMGCR. These targets play an important role in the PPI network and KEGG signaling pathway, and they have a significant impact on glucose and lipid metabolism disorders and inflammation . Binding energy ≤ −5.0 kJ/mol was used as the basis for screening hypoglycemic activity. The results show that the binding energy of all active ingredients to protein was less than −5 kJ/mol, which further indicated that the active ingredients had strong binding activity to protein, expect Poricoic acide A [α, and the highest binding affinity (-11.2 kJ/mol) was observed in Atractylol III and AKT1 , indicating that HJJPD can inhibit the increase of liver weight to some extent [P < 0.05). In addition, the liver/body weight ratio of mice in the HJJPD treatment group was significantly lower than that in the model group (P < 0.05). Obesity is an important risk factor for NAFLD, and the effects of HJPD on mice body and liver weight are shown in e extent . The livBlood biochemical index can provide the information of various ions, sugars, lipids, proteins, enzymes, hormones, and various metabolites, which is conductive to the determination of treatment effect. α, AKT1, PPARG, and PTGS2) predicted by network pharmacology were estimated by RT-qPCR . Compared with the model group, the mRNA expression levels of PPARG, TNF-α, AKT1, and PTGS2 in the HJJPD-treated groups and the positive control group were significantly lower than those in the model group (P < 0.05). These results suggest that HJJPD has protective effects on NAFLD by inhibiting inflammatory factors, glucose, and lipid metabolism.To explore the effect of HJJPD on NAFLD, relevant signaling pathways . Molecular docking is an important method to realize structure-based drug design and screening by studying the interaction between ligand molecules and receptor molecules, predicting their affinity and binding mode [α, and the highest binding affinity (−11.2 kJ/mol) was observed in Atractylol III and AKT1  and top 10 target proteins . These results are consistent with those reported by Wang et al.  and Zhu α, AKT1, and PTGS2 for validation purposes. The experiment results show that HJJPD  could obviously inhibit the mRNA expression levels of PPARG, TNF-α, AKT1, and PTGS2 in the liver and adipose tissues, indicating that HJJPD can regulate the inflammatory response and lipid metabolism and reduce the role of hepatic steatosis [Subsequently, NAFLD mice induced by HDF are applied to further ascertain the function of HJJPD in the amelioration of NAFLD by the validation experiment. When the synthesis and secretion of TC in hepatocytes are damaged and cannot be balanced, lipids rapidly deposit in hepatocytes and cannot be excreted, leading to hepatocyte disease and nonalcoholic fatty liver . A largeteatosis . These eα, AKT1, and PTGS2 in the liver tissues. All in all, HJJPD could ameliorate HFD-induced NAFLD by regulating the inflammatory response and lipid metabolism and decreasing levels of liver-related indexes and the role of hepatic steatosis. This study provides a scientific basis for the further analysis of the clinical application of CCT in NAFLD. However, the further downstream mechanism of HJJPD treatment still needs to be investigated. Additionally, to develop more inexpensive and safer clinical applications, we need to analyze the active components of HJJPD and explore how HJJPD treats NAFLD using different signaling pathways related to inflammation and lipid metabolism.Taken together, the present study puts forward for the first time a comprehensive strategy that combines pharmacological experiments and network pharmacology methods to explore the material basis of HJJPD and its possible mechanisms of the active components of HJJPD against NAFLD. Through active ingredient screening, target prediction, PPI network construction, KEGG pathway, GO biological process analysis, and experimental verification, HJJPD protective mechanism for NAFLD was clarified. It has been demonstrated that inflammatory response- and lipid metabolism- related signaling pathways were identified as the critical signaling pathways mediating the therapeutic effect of the active bioactive ingredients on NAFLD. HJJPD  could significantly decrease the liver wet weight, liver/body ratio, and the levels of TC, TG, AST, ALT, and HDL in serum, and reduce the mRNA expression levels of PPARG, TNF-


Premature ovarian insufficiency, characterized by ovarian infertility and low fertility, has become a significant problem in developed countries due to its propensity for late delivery. It has been described that the vital role of lncRNA in the development and progression of POI. The aim of this work was to create a POI-based lncRNA–mRNA network (POILMN) to recognize key lncRNAs. Overall, differently expressed mRNAs (DEGs) and differently expressed lncRNAs (DELs) were achieved by using the AnnoProbe and limma R packages. POI-based lncRNA–mRNA network (POILMN) construction was carried out using the tinyarray R package and hypergeometric distribution. To identify key lncRNAs, we used CentiScaPe plug-in Cytoscape as a screening tool. In total, 244 differentially expressed lncRNAs (DELs) and 288 differentially expressed mRNAs (DEGs) were obtained in this study. Also, 177 lncRNA/mRNA pairs (including 39 lncRNAs and 86 mRNAs) were selected using the hypergeometric test. Finally, we identified four lncRNA  intersections by topological analysis between two centralities (degree and betweenness), and we explored their subnetwork GO and KEGG pathway enrichment analysis. Here, we have provided strong evidence for a relationship with apoptosis, DNA repair damage, and energy metabolism terms and pathways in the key lncRNAs in our POI-based lncRNA–mRNA network. In addition, we evaluated the localization information of genes related to POI and found that genes were more distributed on chromosomes 15, 16, 17, and 19. However, more experiments are needed to confirm the functional significance of such predicted lncRNA/mRNA. In conclusion, our study identified four long non-coding RNA molecules that may be relevant to the progress of premature ovarian insufficiency. Premature ovarian insufficiency (POI) is a clinical condition exhibiting symptoms of ovarian hypofunction before the age of 40 . It is cin vivo (Long non-coding RNAs (lncRNAs) are broadly classified as transcripts longer than 200 nucleotides that are 5′ capped and polyadenylated like most mRNAs, yet this class of transcripts has limited coding potential . Becausein vivo . Additioin vivo , 1. Therin vivo . The ceRin vivo , polycysin vivo , and impin vivo . With inhttps://www.ncbi.nlm.nih.gov/geo/) was searched using keywords such as “premature ovarian insufficiency,” “POI,” “granulosa cells,” and “Homo sapiens.” The GSE135697 dataset was selected for further study. The GSE135697 dataset  included lncRNA and mRNA expression profiles consisting of 10 POI samples and 10 control samples. The profiling construction and test of the datasets were authorized by the local research ethics committee.In order to obtain the microarray analysis, the public database Gene Expression Omnibus (GEO)  mRNAs and lncRNA were defined as FDR <0.05 and log2|fold change| > 1.Preprocessed data were acquired from GEO using the R package “GEOquery”. After getting the expression matrix, and subsequently, according to the annotation profile recorded in the “AnnoProbe” package (version 0.1.6), probesets were annotated to filter out the duplicate and unannotated probes and then separated into two categories: protein-coding dataset and lncRNA dataset. Log-transformed intensities were quantile normalized using the “normalizeBetweenArrays” function in the “limma” package of R. Then, the limma package was used to identify differentially expressed mRNAs and lncRNAs, respectively. The There is growing evidence that POI was judged to be related to the genetically heterogeneous disorder. The chromosomal location and the starting and ending positions were assessed using the R package “AnnoProbe” (version 0.1.6). The R library “RIdeogram” was used to visualize data along the chromosomes of differentially expressed mRNAs and lncRNAs.http://starbase.sysu.edu.cn) was used to extract lncRNA–miRNA associations from HITS-CLIP and PAR-CLIP experiments. Sequence-predicted miRNA–mRNA pairs were obtained from miRTarBase (https://mirtarbase.cuhk.edu.cn/). The processed relation pairs are selected as the background relation pairs for the hypergeometric distribution.Starbase v3.0 , biological processes (BPs), and cellular components (CCs).Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the DEGs sifted out in the POILMN and lncRNA subnetwork was performed and visualized using the R package clusterProfiler (V4.2.2) . KEGG paTo explore the central nodes of the POILMN network, we performed a topological analysis of DELs and DEGs and calculated using the CentiScaPe plug-in Cytoscape. We focused on two main topological parameters: “degree” and “betweenness.” Retain the topped-eight lncRNA of each parameterization and those overlapped were chosen as hub genes for the follow-up stage.Through the implementation of the previous approach using a hypergeometric test, we obtained all the key lncRNAs and their adjacent mRNA neighbors. At the same time, we also get the overlapped miRNAs that they commonly shared. Ultimately, based on ceRNA theory, we imported a triple network into Cytoscape software to visualize it.To investigate the intracellular localization of key lncRNAs in topological analysis, we used a web-based public platform lncLocator, for prediction. Target lncRNA sequences were downloaded from NCBI in nucleotide FASTA format. Bar plotting was performed using R with the ggplot2 (V3.3.5) package.p < 0.05, including 93 upregulated and 151 downregulated, in the POI granulosa cells in the test compared to the control, as shown in the volcano plot  and 502,653 miRNA–mRNA interaction pairs . Total DELs/DEMs were matched into those two interaction pairs, and then 177 lncRNA/mRNA pairs (including 39 lncRNAs and 86 mRNAs) were selected using the hypergeometric test with p < 0.05) were significantly enriched in the GO analysis. The top four GO terms in BP, MF, and CC are listed in To obtain a better understanding of the role of the DEGs in the lncRNA–mRNA ceRNA network, we performed GO classification and KEGG pathway analysis. Results showed that 16 GO terms  in the KEGG pathways analysis, as shown in p ≤ 0.05 adjusted by Benjamini–Hochberg found ten enriched GO terms for molecular function, as shown in Comprehensive rating had eight top results for HCP5, NUTM2A-AS1, SMIM25, and GABPB1-IT1, respectively. For HCP5, a total of eight mRNAs and 36 miRNAs were composed of the subnetwork of the POILMN in As for the NUTM2A-AS1 subnetwork, 13 mRNA and 43 miRNA comprised the subnetwork . KEGG pap < 0.05). Only the top ten GO biological process terms are shown in The GABPB1-IT1 subnetwork was made up of 10 mRNA and 28 miRNA in all . In condThe SMIM25 subnetwork was composed of eight mRNA and 19 miRNA . The enrPOIs are a common disorder of follicular development characterized by hypertrophy of the initial follicle, slowed growth of antral follicles, and selection of the dominant follicle. In our study, we sought to identify these lncRNAs by examining data from POI microchips and performing analyses to determine their potential roles in POILMN.Chromosomal abnormalities have long been recognized as a frequent cause of POI. We restored the differentially expressed mRNAs and lncRNAs to their chromosomal locations and found that they were not only associated with autosomes but also with sex chromosomes. At the same time, it was found that there are a large number of distributions on the long arm of chromosome 15, the short arm of chromosome 16, and chromosomes 17 and 19.The lncRNA/miRNA and mRNA/miRNA pairs were obtained from the starBase and miRTarBase databases, respectively, and the lncRNA–mRNA network was constructed by calculating the hypergeometric distribution using differentially expressed mRNAs and lncRNAs. The POI-based lncRNA–mRNA network (POILMN) was then extracted with 86 mRNA nodes, 39 lncRNA nodes, and 177 edges. Results were analyzed to determine putative functional POI biomarkers.For the GO term enrichment analyses of DEGs in the POILMN, we observed a large proportion in the number of counts in the category of biological process (BP), such as “apoptotic process,” “cellular response to DNA damage stimulus,” and “protein transport.” Considering of its GC-related diseases, some previous studies confirmed that decreasing apoptosis of granulosa cells could improve the function of the ovary in POI mice . A studyIntriguingly, the most enriched KEGG pathway was “metabolic pathways.” Aside from lower serum AMH levels and higher FSH levels, we also retrieved some metabolism-related case-control studies of POI. These association studies pointed out that serum concentrations of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were significantly higher in the POI group compared with a healthy matched control group . AnotherSeveral carbohydrate metabolism-related pathways were also enriched, including “glycosaminoglycan biosynthesis − chondroitin sulfate/dermatan sulfate” and “N-glycan biosynthesis.” Some studies have reported that glycosaminoglycan chondroitin-4-sulfate may play a role in altering gonadotrophin-stimulated and basal progesterone secretion in follicles during the differentiation of granulosa cells . “HIF-1 We performed a topology analysis of lncRNAs, calculated topological parameters (betweenness and degree), and identified four candidate lncRNAs  that may potentially affect POI susceptibility.The KEGG pathway of “vasopressin-regulated water reabsorption” was enriched in the ceRNA subnetwork of HCP5. Studies have shown that exposure to high doses of PFOA increases the risk of premature ovarian insufficiency by reducing pituitary expression in the suprachiasmatic nucleus (SCN); this implies a possible connection between POI and vasopressin in some way . In addiThe KEGG “mTOR signaling pathway” and GO term “autophagy” were enriched in the ceRNA subnetwork of NUTM2A-AS1. Autophagy is an evolutionarily conserved cellular process controlled through a set of essential autophagy genes (Atgs). As an important player in autophagy, mTOR is essential for autophagosome formation and necessary for the closure of isolation membranes of autophagosomes. The activated mTOR pathway stimulates the proliferation of granulosa cells  and alsoFor GO term enrichment analysis, the “oxidation-reduction process” was enriched in the ceRNA sub-network of GABPB1-IT1. Oxidative stress-induced granulosa cell (GC) death represents a common reason for follicular atresia, which can cause amenorrhea beforehand. As for the KEGG pathway “glycolysis/gluconeogenesis,” a recent study showed that the energy stress-induced lncRNA ZNF674-AS1 regulates GC proliferation and glycolysis, possibly contributing to follicular dysfunction .There are also glucose metabolism pathways enriched in SMIM25 KEGG analysis, such as “glycolysis/gluconeogenesis” and “propanoate metabolism,” that further emphasize the relationship between POI and energy metabolism. By comparing the analysis results of GO enrichments, we found that the “extracellular exosome” term was enriched. Exosomes are extracellular vesicles that mediate cellular communication in health and disease. It has also been shown that exosomes contain messenger RNAs (mRNAs) and microRNAs (miRNAs), which can be delivered unidirectionally and functionally between cells . Recent In brief, our research provided a global view of ceRNA, lncRNA, and mRNA with potential implications for the onset and development of POI. Nevertheless, further longitudinal studies are necessary to extend and explore these potential lncRNAs.


Compound Turkish gall ointment (CTGO) has a long history of being widely used as a folk medicine in Xinjiang for the treatment of eczema. CTGO is currently in the pre-investigational new drug application stage, but its pharmacological mechanisms of action have not yet been clarified.First, a sensitive and reliable ultra-high performance liquid chromatography-Q exactive hybrid quadrupole-orbitrap high-resolution accurate mass spectrometry (UHPLC-Q-Orbitrap HRMS) technique was established. Second, an integrative strategy of network analysis and molecular docking based on identified and retrieved ingredients was implemented to investigate the potential targets and pathways involved in the treatment of eczema with CTGO. Finally, Sprague–Dawley (SD) rats with eczema were prepared to verify the predicted results. The skin conditions of the rats were observed, evaluated, and scored. Skin tissues were observed by hematoxylin–eosin (HE) staining, and the levels of serum interferon-γ (IFN-γ) and interleukin-4 (IL-4) were determined by enzyme-linked immunosorbent assay (ELISA). The expression levels of toll-like receptor 4 (TLR4), nuclear factor kappa-B p65 (NF-κB p65), interleukin-1β (IL-1β), and tumor necrosis factor-α (TNF-α) were detected by real-time quantitative polymerase chain reaction (RT-qPCR).A total of 29 compounds were identified. We found 38 active components and 58 targets for the treatment of eczema, which included 118 signaling pathways related to inflammation, immunity, and apoptosis. CTGO significantly improved the skin surface and histopathological characteristics of eczema-affected rats, downregulated the expression of IL-4, TLR4, NF-κB (p65), IL-1β, and TNF-α, and upregulated the expression level of IFN-γ.We predicted and validated our prediction that CTGO may be used to treat eczema by affecting the TLR4/NF-κB signaling pathway, which provides guidance for future experimental studies. Eczema is a chronic inflammatory skin disease with exudative tendency and clinical manifestations including erythema, blisters, erosion, and pruritus . Modern We systematically expounded the possible targets and related pathways of CTGO in treating eczema by integrating UHPLC-Q-Orbitrap HRMS, network analysis, molecular docking analysis, and experimental evaluation using molecular biology. Figure Low , medium , and high  dose CTGO were purchased from NEW CICON Pharmaceutical Co., Ltd.; Gallic acid , Ellagic acid , and β,β-Dimethylacrylalkannin  were purchased from China Institute for Food and Drug Control; Gallic acid methyl ester  and Ethyl gallate  were purchased from Chengdu Pufei De Biotech Co., Ltd.; L-shikonin (Batch No. 110769–200506) was purchased from China Institute for the Control of Pharmaceutical and Biological Products; Methanol and acetonitrile of HPLC grade were purchased from Sigma-Aldrich Company. All other reagents were of analytical grade and supplied by Tianjin Beilian Fine Chemicals Development Co., Ltd. Compound dexamethasone acetate cream (20201024X) was purchased from China Resources Sanjiu Medical and Pharmaceutical Co., Ltd.; 2, 4-dinitrochlorobenzene  was purchased from Shanghai Jiudin Chemical Technology Co., Ltd.; IL-4 and INF-γ test box  were purchased from Shanghai Enzyme Linked Biotechnology Co., Ltd.; the PCR kit (AQ601-01) was purchased from Beijing Quanshijin; the microscope (EQ2016-037) was purchased from Leica, Germany; the Multiskan FC was purchased from Thermo Fisher; and the electronic balance (CPA124S) was purchased from Sartorius, Germany.Sixty Sprague–Dawley (SD) rats  were purchased from the Laboratory Animal Center of Xinjiang Medical University (License number: SCXK (new) 2018–0002). All of the rats were fed in an environment free of specific pathogens, at a temperature of 20–26 °C, humidity 40%– 70%, artificial light, 12-h light/dark cycle, and had free access to food and water.http://tcmspw.com/index.php/), CNKI (https://www.cnki.net/), CTD (http://ctdbase.org/), ETCM (http://www.tcmip.cn/ETCM/index.php/Home/Index/The following databases were used: TCMSP (http://47.100.169.139:8000/tcmid/), BATMA.), TCMID (http://bionet.ncpsb.org.cn/batman-tcm/), GEO (https://www.ncbi.nlm.nih.gN-TCM (https://go.drugbank.com/), STRING (https://string-db.org/), Pu.ov/geo/), DrugBank (https://pubchem.ncbi.nlm.nih.gov/), and PDB (http://www1.rcsb.org/). The software Cytoscape 3.7.2, R3.6.1 language, Chem3D, PyMOL, AutoDock Vina-1.5.6, and BIOVIA Discovery Studio 2020 were used.bChem  using a Kromasil Classic 100–5-C18 column  at 30 °C, with a flow rate of 1.0 mL/min and a wavelength of 300 nm. The mobile phase consisted of water containing 0.1% formic acid (solvent system A) and acetonitrile (solvent system B). Gradient elution was conducted as follows: 0–5 min, 5% B; 5–45 min, 5–12% B; 45–50 min, 12% B; 50–80 min, 12–20% B; 80–95 min, 20–25% B; 95–105 min, 25–67% B; 105–115 min, 67–70% B; 115–125 min, 70–75% B; 125–135 min, 75% B. Ten microliters of the sample solution was injected for analysis.2 resolution was 17,600 FWHM (200 m/z). The Xcalibur 4.0 software package was used for data acquisition and analysis .Mass detection was performed using an UHPLC-Q-Orbitrap HRMS equipped with a Dual ESI source operating in both positive and negative modes with the following operating parameters: ESI spray voltage, –2.8 kV ; sheath gas, 40 arb; auxiliary gas, 10 arb; air curtain gas (CUR), 35; ion source temperature (heat temp), 350 °C; capillary temperature, 300 °C; –70 V; focusing voltage (FP), –350 V; and DP2, –10 V. The data dependent acquisition (DDA) mode was adopted for sample analysis; the collection range of the q-orbitrap was 100–1500 m/z, and the fragment ion scanning range was 50–1500 m/z. The collision gas (NCE): 20, 40, 60. The mass spectrometry (MS) resolution was 70,000 full width at half maximum (FWHM) (200 m/z), and the MSTo prepare the sample, 0.05 g of Turkish gall was weighed and placed into a conical flask. Next, 25 mL of 80% methanol was added before a 1-h reflux in a water bath at 75 °C. Then, a pipette was used to transfer 1 mL of the supernatant into a 5 mL volumetric flask. Simultaneously, 0.1 g of Comfrey was weighed precisely and placed into another conical flask, before adding 50 mL of chloroform and subjecting it to a 1 h reflux in a water bath at 75 °C. The sample was then filtered, and the solvent was evaporated in the water bath. The residue was transferred into the abovementioned 5-mL volumetric flask with approximately 4 mL of acetonitrile to bring the total volume to 5 mL.“Turkish gall” and “Comfrey” were searched for in the TCMSP, CTD, TCMID, ETCM, and BATMAN-TCM databases and the literature to obtain the components of Turkish gall and Comfrey. These agents were combined with the compounds identified by UHPLC-Q-Orbitrap-HRMS to build the active ingredient database of CTGO. Targets corresponding to the components were obtained through the TCMSP and BATMAN-TCM databases, and a target database of CTGO was constructed. “Eczema” was searched in the GEO and DrugBank databases to obtain eczema targets. R 3.6.1 language software was used to obtain the intersection targets of drugs and diseases.To clarify the relationship between intersection targets, an intersection target PPI network of eczema and CTGO components was constructed and analyzed using the STRING database. Species were defined as Homo sapiens. PPIs with a confidence score > 0.40 were selected and topology analyses were conducted to ensure the accuracy of the results. The PPI network was imported into the Cytoscape 3.7.2 software for use with PPI topology analysis.q < 0.05), the top 10 GO biological processes, cellular composition, and molecular functions were selected to draw bubble maps; the intersection targets of CTGO and eczema were analyzed by KEGG enrichment. According to the number and significance of gene enrichment (q < 0.05), the top 20 pathways were selected and bar graphs were drawn. The size of the bubbles and strips in the figure represents the number of enriched genes on this pathway, and the color difference of the bubbles and strips represents the level of enrichment of target genes on this pathway.GO enrichment analysis was performed on the intersection targets of CTGO with eczema using R language software. According to the number and significance of gene enrichment  in the PPI network. First, the composition and target files were downloaded from PubChem and PDB. Next, energy minimization of the component file was completed by Chem3D, and dewatering and impurity removal of the target file were completed by PyMOL. The file was then converted to PDBQT format using AutoDock Vina. The active pocket of the target was determined, molecular docking was performed, and binding energy values were obtained. The best docking model diagram was drawn by BIOVIA Discovery Studio. Finally, the binding ability was evaluated by the affinity of the component and the target.Sixty rats were randomly divided into a normal group, a model group, a positive group (compound dexamethasone acetate cream), a CTGO high-dose group, a CTGO medium-dose group, and a CTGO low-dose group, with 10 rats per group. The rats in all groups, except for the normal group, were treated with 7% DNCB solution by rubbing the solution on the back to establish the eczema model. The hair on the neck (A: 2 cm × 2 cm) and back (B: 4 cm × 4 cm) of the animals was removed using an electric shaver. The rats were sensitized by applying 100 μL of 7% DNCB acetone solution with a pipetting gun on the skin of site A. Severe pruritus, frequent scratching, and rolling behaviors were observed in rats, lasting for approximately 2 h. After 1 week, 200 μL of 7% DNCB acetone solution was applied to site B for excitation. The rats were stimulated once every 5 days, and in each stimulation, severe pruritus could be seen in rats, with frequent scratching and rolling behavior. Erythema, papules, edema, scratches, and desquamation gradually appeared on the skin at site B. After each stimulation, the skin lesions were recorded and scored. After six sessions of stimulation, erythema, papules, scab, and exudation appeared in skin lesions on the back of each rat, at which point the stimulation was stopped, indicating that the model had been successfully established .Each group was administered a low (0.035 g/g), medium (0.07 g/g), or high (0.14 g/g) dose of CTGO, and the positive group was administered compound dexamethasone acetate cream . The normal and model groups were administered with saline. After smearing the experimental drug, 2–3 layers of medical gauze were wrapped and fixed with a non-irritating adhesive tape. After 4 h, the covering was removed and washed with warm pure water for continuous administration for 14 days.After the final administration, the rats were fasted with water for 12 h. The rats were mildly anesthetized with 1% sodium pentobarbital . Blood samples were collected from the abdominal aorta and placed in a centrifuge tube for 30 min at 3000 rpm at 4 °C, before storing the supernatant at –20 °C. One part of the obtained skin tissue was immersed in 10% neutral formalin for fixation, and the other part was stored at − 80 °C.On days 1, 5, 10, 15, 20, 25, 30, and 35 (administration D0) of modeling, and on days 0, 9, and 14 of administration, the grades of erythema, edema, exudation, desquamation, liche-like change, desquamation were scored from 0 to 2. A score of 0 represents no symptoms; 1 represents mild symptoms; and 2 represents significant symptoms After 14 days of administration, the skin conditions were photographed observed with the naked eye.Skin tissue was removed from 10% neutral formalin solution, dehydrated, permeated, paraffin impregnated, embedded, sectioned, stained, and sealed. Histomorphological observation was performed with a microscope, and radiographs were taken.The levels of IFN-γ and IL-4 in the serum of rats were determined according to the instructions of the ELISA kit.−△△CT method was used to analyze the difference in target gene expression between the control group and test groups.The mRNA expression levels of TLR4, NF-κB (p65), IL-1β, and TNF-α in skin tissue samples were detected by RT-qPCR. RNA was extracted, its purity was determined, and cDNA was obtained by reverse transcription. PCR upstream and downstream primers were added , IL1β, and TLR4. In PPI topology analysis, the six topological eigenvalues of “closeness centrality (CC),” “betweenness centrality (BC),” “eigenvector centrality (EC),” “local average connectivity (LAC),” “degree centrality (DC),” and “network centrality (NC)” were used as filter conditions. Targets with topological eigenvalues greater than their corresponding medians were used as core targets, and two rounds of analysis were performed. Fifteen core targets were obtained in the first round and four were obtained in the second round, as shown in Fig. PPI topology analysis results showed that after importing the intersection targets into the STRING data platform, the PPI relationship between the intersection targets was obtained. The PPI analysis network was obtained using Cytoscape 3.7.2 for topology analysis of the relationship. The network consisted of 58 nodes and 390 edges. The average node degree value was 13.4, and the PPI enrichment q < 0.05) GO functional enrichment items were obtained, including 1316 biological processes (BPs), 75 molecular functions (MFs), and 29 cellular components (CCs), as shown in Fig. q < 0.05) signaling pathways were obtained, as shown in Fig. GO and KEGG enrichment analyses and visualization processing were performed on 58 intersections of CTGO and eczema using the Bioconductor bioinformatics software package. GO functional annotation showed that 1420 . Compared to the model group, the apparent scores in each administration group were significantly decreased (p < 0.01), as shown in Table After 14 days of administration, the back skin of rats in the normal group was pale red, delicate, and tender, with a soft texture. The back skin lesions of the rats in the model group were obvious, with skin erythema, infiltration, scales, scabs, rough and thickening texture, pigmentation, and scratches, which still met the diagnostic criteria for chronic eczema. Regarding the observation record of apparent indicators, as shown in Fig. The thickness of the cuticle, epidermis, and dermis in the normal group was normal. Model group rats showed chronic eczema, including hyperkeratosis, parakeratosis, hypertrophy of the granular layer, hypertrophy of the spinous layer, and infiltration of numerous inflammatory cells in the epidermis/dermis. After 14 days of administration, hyperkeratosis, parakeratosis, hypertrophy of the granular layer, and hypertrophy of the spinous layer were inhibited in each administration group, and the infiltration of inflammatory cells in the epidermis/dermis was reduced. The results are shown in Fig. . Among t#p < 0.05) and the levels of IL-4 in the model group were significantly increased (#p < 0.05). Compared to the model group, the level of IFN-γ in the CTGO group was significantly increased (**p < 0.01) and that of IL-4 was significantly decreased  , and the level of IL-4 in the low dose group decreased significantly (*p < 0.05).Compared to the normal group, the levels of IFN-γ in the model group were significantly decreased (01) Fig. . Compare##p < 0.01, ###p < 0.001, or ####p < 0.0001). Compared to the model group, the contents of IL-1β and TNFα in the skin tissue of rats in the positive group and CTGO low-, medium-, and high-dose groups were significantly decreased , and the contents of TLR4 and NF-κB in the skin tissue of rats in the CTGO low-, medium-, and high-dose groups were significantly decreased . Compared to the positive group, the contents of TLR4 and NF-κB in the skin tissue of rats in the medium- and high-dose CTGO groups were significantly decreased   Fig. .Fig. 12mTCM compounds have multi-component and multi-target synergistic effects, and have been widely used in clinical practice because of their clear curative effect and minor side effects. CTGO has shown good clinical efficacy in the treatment of eczema, but its mechanism of action remains unclear. Based on network pharmacological analysis, we investigated the pharmacodynamics and action mechanism of CTGO in a rat model of eczema.In this study, a combined strategy of phytochemistry, network analysis, molecular docking, and basic experiments was used to assess the active constituents and potential molecular mechanisms of CTGO on eczema. First, the chemical composition of CTGO was characterized by UHPLC-Q-Orbitrap HRMS for the first time. A total of 29 constituents, mainly belonging to polyphenols, naphthalene quinones, and anthraquinones, were identified. Due to the small number of chemical components identified by mass spectrometry, no more components were identified. To make the results of network pharmacological prediction and analysis more comprehensive, we performed a database and literature search of the chemical constituents of gallic gall and Comfrey, and retrieved 57 chemical constituents. The components identified by mass spectrometry were combined with the retrieved components, and after removing duplicates, 77 components were finally obtained and used as a basis for network pharmacological analysis.Staphylococcus aureus, Pseudomonas aeruginosa, Candida albicans, and E. coli [The component-target-pathway network contained 38 active ingredients. The common active components of gallic gall and Comfrey are palmitic acid and β-sitosterol. Their common targets are the core targets of TNF and IL-1β, which rank highly in degree value. The top two components in degree value were gallic acid and ellagic acid, which are the main components of gallic gall, and have 11 common targets, namely, TNF, TGFβ1, RELA, PTGS1, PTGS2, NOS2, MMP9, IL-1β, CYP1B1, CYP1A1, and Alb. All of the targets are closely related to inflammatory, immune, and metabolic reactions. Shikonin is the main chemical component of Comfrey; it can act on nine eczema-related targets, among which TNF and PTGS2 are the common targets of shikonin, gallic acid, and ellagic acid. Gallic acid has a good antibacterial effect, and can effectively inhibit  E. coli . Gallic  E. coli , 15. Ell E. coli . Studies E. coli . Shikoni E. coli . Studies E. coli .The PPI network contains 58 core targets for the treatment of eczema, reflecting the multi-target characteristics of CTGO in the treatment of eczema. TNF-α, IL1β, and IL-4 are important cytokines in the process of skin immunity and inflammation. Under the action of allergens in the skin system, numerous inflammation-mediated factors, such as TNF-α, IL1β, and IL-4, are secreted during epidermal keratinization, all of which interact with each other in the pathogenesis of eczema, thus influencing the development and prognosis of the disease , 21. TLROur molecular docking results showed that the overall scores of TNF, TLR4, IL1β, and Alb when docking with four key components were all lower than –5.0 kcal/mol, which suggested that they may play an essential role in CTGO against eczema.The 38 active ingredients act on 58 targets related to eczema; all of these 58 targets are connected with 118 pathways closely related to inflammation and immunity. All of the above components, targets, and pathways form a network, which may be the mechanism by which CTGO functions to treat eczema. The toll-like and NF-κB pathways are among the first 30 pathways significantly associated with CTGO in the treatment of eczema and are closely related to inflammatory responses. The toll-like pathway affects the NF-κB pathway through regulating NF-κB, and the NF-κB pathway then regulates the downstream of the toll-like pathway. As NF-κB connects the two pathways, they are closely related and mutually regulated. Eight of the 58 intersection targets were enriched on the Toll-like pathway, namely TNF, IL1B, TLR4, RELA, CD14, MAP2K1, RAC1, and IRF3. Seven of the 58 intersection targets were enriched in the NF-κB pathway, namely TNF, IL1B, TLR4, RELA, CD14, PTGS2, and PLAU. PPI topology analysis yielded four core targets, namely TNF, IL1β, TLR4, and Alb, of which TNF, IL1β, and TLR4 were key upstream and downstream targets involved in both of the above pathways. Therefore, we speculate that the toll-like and NF-κB signaling pathways may be the main way by which CTGO functions in the treatment of eczema. The TLR4/NF-κB signaling pathway was selected for validation, and TLR4, NF-κB, TNF-α, and IL1β were finally selected as indicators to be validated in this pathway.Toll receptors are a class of highly conserved pattern recognition receptors. TLR4 recognizes various ligands of microorganisms and undergoes dimerization upon ligation. MyD88 and non-MyD88 pathways activate mitogen-bound protein kinase, activate NF-κB, upregulate inflammatory cytokines and chemokines, and induce inflammation. These pathways play an important role in the pathogenesis of eczema , 25. NF-In this study, the rat eczema model was induced by DNCB. When the body is re-exposed to the same antigen after being stimulated by DNCB through the skin, a type IV allergic reaction characterized by skin damage occurs. Repeated stimulation can produce clinical manifestations similar to eczema, and the coincidence degree with the main symptoms of eczema in Chinese medicine is > 70%. Following establishment of the model, many indicators can be used to judge whether the model has been established successfully and whether the drug has a therapeutic effect after administration. Among them, the apparent indexes belong to the core indexes, such as the skin lesion area, itching condition, fur gloss, and skin erythema and edema. Pathological indexes are directly related indexes, and local histopathological changes of skin are reliable indexes to evaluate the degree of skin lesions. Biochemical indexes are indirectly related indexes, and IL-4 and other biochemical indexes will increase after the animal eczema model has been successfully established . After CImmune imbalance, especially Th1/Th2 imbalance, plays an important role in the pathogenesis of eczema. IFN-γ is mainly secreted by Th1 cells and can inhibit IL-4 secretion by Th2 cells, as well as inhibit IgE production by B cells. IL-4 is mainly secreted by Th2 cells and mainly inhibits Th1 cell function, and promotes IgE production by B cells, which inhibit and antagonize each other and maintain the Th1/Th2 balance. The expression levels of IFN-γ and IL-4 in normal subjects maintained a relatively balanced state, which is lost in patients with eczema. The experimental results showed that CTGO could significantly reduce IL-4 levels and increase IFN-γ levels, suggesting that CTGO may play a role in the treatment of eczema by promoting Th1/Th2 homeostasis by down-regulating IL-4 levels and up-regulating IFN-γ levels , 31.Patients with eczema have a severe inflammatory response, and many inflammatory factors play a key role in the occurrence and development of eczema. The TLR4/NF-κB signaling pathway is involved in the inflammatory response, where TLR4 recognizes endogenous ligands and is activated via identifying related ligands, and the signal conduction through the MyD88 pathway leads to the activation of NF-κB. This signaling ultimately results in the production of a large amount of IL-1β, TNF-α, and other inflammatory factors, which promote cell proliferation and repair. However, with the excessive activation of NF-κB comes excessive release of these inflammatory factors; then, the responsive activation of TLR4 forms a vicious cycle, which leads to uncontrollable inflammatory response. Consequently, the epidermis produces excessive inflammatory reactions, and the tissue organs are damaged, which result in the occurrence and development of eczema. The results of the animal experiments indicated that CTGO could significantly reduce the expression of IL-1β, TNFα, TLR4, and NF-κB. These changes in key genes suggest that the mechanism of CTGO in treating eczema may be related to the effect of the TLR4/NF-κB signaling pathway , 33.In conclusion, our experiments showed that CTGO could reduce the expression of IL-1β, TNFα, TLR4, and NF-κB, and significantly promote the expression of IFN-γ, which is consistent with the results of the prediction of network pharmacology and molecular docking. The mechanism of CTGO in treating eczema may be related to regulating related inflammatory factors, promoting the Th1 and Th2 immune balance, and affecting the TLR4/NF-κB signaling pathway.