Combinatorial Chemistry & High Throughput Screening - Volume 26, Issue 4, 2023

Background: Stomach cancer, also known as gastric adenocarcinoma, remains the most common and deadly cancer worldwide. Its early diagnosis and prevention are effective to improve the 5-year survival rate of the patients. Therefore, it is important to discover specific biomarkers for early diagnosis and drug treatment. This study investigates the potential key genes and signaling pathways involved in gastric cancer. Methods: The gene expression profiles, GSE63089, GSE33335, and GSE79973, were retrieved for the identification of Differentially Expressed Genes (DEGs) within a total of 80 gastric cancer samples and 80 normal samples. A total of 1423 uP- and 1155 downregulated genes were screened for overlapping DEGs visualized via Venn diagrams along with 58 upregulated and 43 downregulated genes. These overlapping DEGs were evaluated with Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and Protein-Protein Interaction (PPI) network analysis. Using DAVID software, we identified several genes enriched in both GO and KEGG analyses. PPI analysis was performed with STRING software, and 3 submodules were obtained with Cytoscape software. Then, we used Cytohubba with 12 classification methods to select candidate hub genes. The group 1 genes enriched in GO and KEGG pathway intersected with group 2 genes, which were approved by nine algorithms, and group 3 genes clustered in three submodules. 9 hub genes were intersected from group 1/2/3 genes and the prognostic values were estimated through GEPIA. We found that the LUM and COL1A1 expression levels and survival outcomes displayed a favorable prognostic value (P-value = 0.013 for LUM and P-value =0.042 for COL1A1). Results: Finally, 5 machine learning methods were employed for the validation of two hub genes (COL1A1, LUM) to distinguish between the cancer samples and non-cancer samples. The accuracy of XGBoost was estimated to be 0.9375, and the precision and specificity as 1.000. The highest recalls of LR and MLP were 1.0000, and the AUC was 1.0000. In the test set GSE65801, the accuracy of all models was greater than 80%, and the XGBoost model obtained the highest prediction accuracy of 0.8906. The precision of 0.9301 and the specificity of 0.9375 were obtained. The highest recall of MLP was 0.8750 and AUC was 0.9082. The correlation of prognostic indicators with the tumor-infiltrating immune cell levels was analyzed using TIMER. Conclusion: The identified hub genes explored in this study would enhance the understanding of the molecular mechanism of gastric cancer and may be regarded as a potential therapeutic target as assessed by integrating bioinformatics and machine learning methods.

Background: Tuberculosis is one of the oldest known infectious diseases to mankind, caused by Mycobacterium tuberculosis. Although current treatment using first-line anti-tubercular drugs is proven to be effective, an infection caused by resistant strains, as in multidrug-resistant and extensive drug- resistant tuberculosis is still an impending challenge to treat. Objective: Our objective is to focus on reporting benzimidazole derivatives that are targeting mycobacterial membrane biosynthesis, particularly the mycobacterial mycolyl-arabinogalactanpeptidoglycan complexes. From the literature survey, it has been noted that targeting Mycobacterium tuberculosis cell membrane biosynthesis is an effective approach to fight against drug resistance in tuberculosis. Methods: Articles on benzimidazole derivatives as inhibitors of proteins responsible for the biosynthesis of the mycobacterial mycolyl-arabinogalactan-peptidoglycan complex have been selected. Results: By reviewing the anti-tubercular activity of the reported benzimidazole derivatives, we have concluded that a correlation between benzimidazole derivatives and their biological activity is found. It has been noted that benzimidazole derivatives with substitution at N1, C2, C5, and C6 positions have shown a greater affinity towards target proteins. Conclusion: Even though scientific advancement toward the prevention of tuberculosis has been quite significant in the past few decades, infection caused by resistant strains is a major concern. We have collected data on benzimidazole derivatives that inhibit the biosynthesis of mycolic acid, arabinogalactan and, peptidoglycan. From our observations, we conclude that majority of the molecules have given anti-tubercular activity in nanomolar range. Still there are few mycobacterial membrane biosynthesis proteins where benzimidazole as an inhibitor has yet to be explored.

Background: RHBDD1 is an intramembrane serine protease of the rhomboid superfamily that regulates diverse physiological and pathological processes. However, the relationship between RHBDD1 expression, tumor-infiltrating immune cells (TIICs), and cancer prognosis remains unclear. Objective: We comprehensively analyzed the prognostic and immunological significance of RHBDD1 in multiple primary cancers. Methods: RHBDD1 expression was investigated using Oncomine, TIMER, and UALCAN databases, after which the clinical prognostic value of RHBDD1 was assessed with online public databases. In addition, we explored the correlation between RHBDD1 and TIICs by TIMER and GEPIA and investigated the relationship between RHBDD1 expression and chemokines in cancers by TIMER. Results: In general, compared to that in adjacent normal tissue, lower expression of RHBDD1 was found in various cancers and was correlated to pathological stages. Although RHBDD1 showed a protective effect on multiple solid tumors, a high expression level of RHBDD1 was detrimental to the survival of stomach adenocarcinoma patients. RHBDD1 was positively correlated to immune infiltration levels in various cancers, including lung, breast, ovarian, and gastric cancer. Furthermore, gene markers of TIICs, such as tumor-associated macrophages (TAMs), dendritic cells (DCs), and regulatory T cells, were also correlated to RHBDD1 expression. In addition, the RHBDD1 expression level was positively correlated to multiple chemokines in cancers, which could recruit diverse immune cells at the tumor site. Conclusions: RHBDD1, which correlates with immune infiltration, can be used as a potential prognostic biomarker in multiple primary cancers. Specifically, RHBDD1 expression potentially contributes to the recruitment of TAMs and DCs and the regulation of T cell functions in cancers.

Background: Frizzled-8 (FZD8) receptor is a therapeutic target for cancer treatment and recent research has shown that carbamazepine (CBZ) can inhibit this receptor. Objective: In this work, it has been tried to optimize CBZ to enhance its binding capacity to the N6W binding site of FZD8 by using structure-based drug design methods. Methods: CBZ and its 83 derivatives were docked to the N6W binding site of FZD8. Results: Docking results show that two compounds 79 and 82 have the smallest binding energies and are fitted to the N6W binding site. Compounds C79 and C82 have been synthesized by replacing a hydrogen atom of the seven-membered ring in CBZ with benzoate and nicotinate groups, respectively. In addition, docking results show that a trifluoromethyl on one of the phenyl rings is favorable for improving the FZD8 inhibition activity of the molecule. Conclusion: Both molecules C79 and C82 were subjected to molecular dynamics (MD) simulation. MD results show that FZD8-C82 complex is stable and this compound binds to the N6W binding site more strongly than compounds C79 and CBZ.

Background and Objectives: Qingbutongluo pill (QBTLP), a Chinese herbal preparation, has been developed to treat brucellosis for many years with a good therapeutic effect. This study preliminarily explored its potential molecular mechanisms against brucellosis through network pharmacology. Methods: The active ingredients of QBTLP were screened out mainly from the Traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP), and their potential targets were predicted through the PubChem database and Swiss Target Prediction platform. GeneCards, DisGeNET Digsee and the Comparative Toxicogenomics Database (CTD) searched the targets corresponding to brucellosis. Then, the Venn diagram obtained intersection targets of QBTLP and diseases. Protein-protein interaction (PPI) network analysis was performed using the Search Tool for the Retrieval of Interacting Genes database (STRING) and visualized in Cytoscape software. Module analysis of the PPI network and core target identification was performed using the Molecular Complex Detection (MCODE) and the Cytohubba plugins. The Metascape data platform was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on the intersection targets, and then the “active ingredientstargets- pathways” network was constructed using Cytoscape to screen key active ingredients. Results: 19 key active ingredients were identified by network pharmacological, including Baicalein, Cryptopin, etc. The core targets of QBTLP for treating brucellosis contained TNF, TLR4, MAPK3, MAPK1, MAPK8, MAPK14, MMP9, etc. And the main pathways included the Toll-like receptor signaling pathway, NOD-like receptor signaling pathway, TNF signaling pathway, MAPK signaling pathway, Th17 cell differentiation, and IL-17 signaling pathway. Conclusions: This study explored the mechanisms of QBTLP for treating brucellosis, which may provide a scientific basis for the clinical application of QBTLP.

Background: Herpes zoster is one of the most common diseases in middle and old ages, and the incidence rate is constantly increasing. Long-term, severe neuropathological pain continues to afflict the patients, causing trouble and even the inability to live a normal life. Since the occurrence and development of herpes zoster are related to many mechanisms, there is no uniform conclusion and specific treatment method, and only a limited number of people are currently vaccinated against HZ. Objective: This study aimed at exploring the potential mechanism or biomarkers for Herpes zoster. Methods: In this study, a data set GSE165112 containing 12 samples was downloaded, out of which, 6 samples were treated with interferon, and 6 samples were not treated. Differentially expressed genes (DEG) analysis, KEGG, GO enrichment analysis, and GSEA were carried out. Results: A total of 264 DEGs were identified, including 32 uP-regulated DEGs and 232 downregulated DEGs. DEGs are mainly enriched in immune response, inflammatory response, chemotaxis, etc. Four key pathways were found to be related to HZ, including IL2-STAT5 signaling, inflammatory response, TNF-a signaling via NF-ΚB, and IFN-α. Moreover, ten hub genes were also identified. Conclusion: This study shows that exploring DEGs and pathways through bioinformatics analysis is of great significance for understanding the molecular mechanism of HZ, especially the defect of the IFN pathway. It may be helpful in improving the treatment for HZ.

Background: Acute myocardial infarction (AMI) remains one of the most fatal diseases worldwide. Persistent ischemia and hypoxia are implicated as significant mechanisms in the development of AMI. However, no hypoxia-related gene targets of AMI have been identified to date. This study aimed to identify potential genes and drugs for AMI using bioinformatics analysis. Materials and Methods: Two datasets both related to AMI (GSE76387 and GSE161427) were downloaded from the Gene Expression Omnibus to identify differentially expressed genes (DEGs) between AMI and sham mice. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. A protein-protein interaction (PPI) network was constructed to identify hub genes using Cytoscape. Candidate genes were identified by the intersection of hub genes and hypoxia-related genes. Western blotting was used to validate the candidate genes in the AMI mouse model. Furthermore, the Drug-Gene Interaction Database was used to predict potential therapeutic drugs targeting all hub genes. Results: Fifty-three upregulated and 16 downregulated genes closely related to AMI were identified. The DEGs were primarily enriched in protein, heparin, and integrin binding. KEGG analysis suggested that focal adhesion, PI3K-Akt signaling pathway, and extracellular matrix-receptor interaction are crucial pathways for AMI. The PPI network analysis identified 14 hub genes, two of which were hypoxia-related. Several agents were found to have therapeutic potential for AMI. Conclusion: This study suggests that connective tissue growth factors and the collagen family members may be candidate targets in treating AMI. Agents targeting these candidates may be potential treatments.

Objective: The objective of this study is to analyze and verify the main drug components and targets of "Fuzi-Guizhi" in the treatment of osteoarthritis by using the network pharmacology platform. Methods: The integrated pharmacology of "Fuzi-Guizhi" was analyzed by using the platform of integrated pharmacology of traditional Chinese medicine to explore its mechanism in the treatment of osteoarthritis. By establishing an arthritis model in vitro, the pharmacological effect of "aconitecassia twigs" on articular cartilage was evaluated and conducted for molecular docking. Results: 28 candidate active components, 37 compound targets, and 583 osteoarthritis-related potential targets were screened, and 10 key target processes were screened in the protein interaction network model. Enrichment analysis showed that the 10 core targets involved 958 GO biologic function items and 76 KEGG signal pathways, which were mainly related to apoptosis and mitochondrial functional metabolism and "Fuzi-Guizhi" drug-containing serum inhibited the expression of Caspase-3 mRNA and protein in chondrocytes and promoted the synthesis of ATP. Conclusion: Our research is preliminary that the mechanism of action of "Fuzi-Guizhi" may inhibit chondrocyte degeneration by resisting mitochondrial apoptosis, and further experimental research is required to determine.

Objective: Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor of the digestive tract, and its molecular mechanisms have not been fully clarified. This study aimed to evaluate the immune infiltration pattern of esophageal cancer through a gene co-expression network, and to provide biomarkers for immunotherapy of esophageal cancer. Methods: We downloaded RNA-seq data of ESCC samples from GSE53625 and GSE66258 datasets, then assessed the immune score and tumor purity through the ESTIMATE algorithm. Next, a co-expression network was constructed by the weighted gene co-expression network analysis, and the key co-expressed immune- related genes were identified on the basis of existing human immune-related genes. Afterward, we utilized bioinformatics algorithms including GSVA, CIBERSORT, and ssGSEA to clarify the relationship between hub genes and immune infiltration patterns. Finally, these hub genes were used to evaluate the sensitivity to immunotherapy by the subclass mapping algorithm, which were further validated by digital pathology through the Hover- Net algorithm. Results: Sixteen immune-related genes with robust expression characteristics were identified and used to build gene signatures. The expression of gene signature was significantly related to the immune infiltration pattern and immunotherapy sensitivity prediction in patients with esophageal cancer. Consistent with previous studies, genetic changes at the level of somatic mutations such as NFE2L2 were revealed. Conclusion: A total of 16 immune-related genes with the total expression gene signature can be used as biomarkers for immunotherapy of esophageal squamous cell carcinoma. Its molecular mechanisms deserve further study to guide clinical treatment in the future.

Background: Alzheimer's disease (AD) is the most common neurodegenerative disorder that affects the neuronal system and leads to memory loss. Many coding gene variants are associated with this disease and it is important to characterize their annotations. Methods: We collected the Alzheimer's disease-causing and neutral mutations from different databases. For each mutation, we computed the different features from protein sequence. Further, these features were used to build a Bayes network-based machine-learning algorithm to discriminate between the disease-causing and neutral mutations in AD. Results: We have constructed a comprehensive dataset of 314 Alzheimer's disease-causing and 370 neutral mutations and explored their characteristic features such as conservation scores, positionspecific scoring matrix (PSSM) profile, and the change in hydrophobicity, different amino acid residue substitution matrices and neighboring residue information for identifying the disease-causing mutations. Utilizing these features, we have developed a disease-specific tool named Alz-disc, for discriminating the disease-causing and neutral mutations using sequence information alone. The performance of the present method showed an accuracy of 89% for independent test set, which is 13% higher than available generic methods. This method is freely available as a web server at https://web.iitm.ac.in/bioinfo2/alzdisc/. Conclusions: This study is useful to annotate the effect of new variants and develop mutation specific drug design strategies for Alzheimer’s disease.

Background: Asthma is a severe chronic inflammatory airway disease. Kechuanning plaster has excellent efficacy in the treatment of asthma. Objective: The aim of this study was to analyze the molecular mechanisms of Kechuanning plaster in the treatment of asthma. Methods: An asthma model was constructed using Sprague Dawley rats. Differentially expressed genes (DEGs) were screened in three rat groups: the control (normal rats), model (asthma rats), and treatment (asthma rats treated with Kechuanning) groups. After enrichment analysis of the DEGs, the protein-protein interactions (PPIs) of the DEGs were analyzed, and transcription factors and microRNAs (miRNAs) that regulate DEGs were predicted. Finally, western blotting (WB) and immunohistochemical (IHC) analysis was performed to validate protein expression. Results: A total of 745 DEGs were identified and enriched in 93 Gene Ontology terms and 25 Kyoto Encyclopedia of Genes and Genomes pathways. A PPI network, consisting of 224 protein nodes and 368 edges, was constructed. The nuclear factor of activated T cells 2 (NFATc2) was predicted to have binding sites in 61 DEGs. The miRNA-target interaction network included 24 DEGs and 9 miRNAs. WB and IHC analysis demonstrated that the fatty acid-binding protein 5 (FABP5) and the chemokine (C-X-C motif) ligand 3 (CXCL3) had higher expression in the model group and lower expression in the control and treatment groups. Conclusion: We concluded that FABP5, CXCL3, suppressor of cytokine signaling 3 (SOCS3), E1A binding protein P300 (EP300), NFATc2, microRNA 495 (miR-495), and miR-30 may play important roles in treating asthma.

Background: Acute respiratory distress syndrome (ARDS) caused by sepsis presents a high mortality rate; therefore, identification of susceptibility genes of sepsis to ARDS at an early stage is particularly critical. Methods: The GSE66890 dataset was downloaded and analyzed by WGCNA to obtain modules. Then, GO and KEGG analyses of the module genes were performed. Then, the PPI network and LASSO model were constructed to identify the key genes. Finally, expression levels of the screened genes were validated in clinical subjects. Results: We obtained 17 genes merged modules via WGCNA, and the dark module and tan module were the most positively and negatively correlated with sepsis-induced ARDS, respectively. Based on gene intersections of the module genes, 11 hub genes were identified in the dark module, and 5 hub genes were identified in the tan module. Finally, the six key genes were identified by constructing the LASSO model. We further detected the screened genes expression in clinical samples, and as the bioinformatics analysis revealed, the expressions of NANOG, RAC1, TWIST1, and SNW1 were significantly upregulated in the ARDS group compared to the sepsis group, and IMP3 and TUBB4B were significantly downregulated. Conclusion: We identified six genes as the potential biomarkers in sepsis-related ARDS. Our findings may enhance the knowledge of the molecular mechanisms behind the development of sepsisinduced ARDS.

Background: The incidence of sleep disorders is more than 27% in the worldwide, and the development of novel sleep drugs that target GABAA receptors is of great interest. Traditional drug screening methods restrict the discovery of lead compounds, the high-throughput screening system is a powerful means for the lead compounds discovery of sleep drug. Methods: The GABAA1-CHO cell line stably expressing α1β2γ2L was constituted by cotransfection of α1, β2 and γ2L subunits into CHO-T-Rex cells. The high-throughput screening method of membrane potential targeting GABAAR was established and optimized. The optimized method was used to screen the compound library, and the compounds with high activity were obtained. The active compounds were confirmed in vitro by electrophysiological detection technique, and the sleep effects of compounds in vivo were detected by pentobarbital sodium sleep model in mice. Results: A stable cell line expressing human GABAA1 receptor in CHO-T-Rex cells was generated and used to establish a functional high-throughput screening assay based on the measurement of membrane potential changes in living cells by fluorometric imaging plate reader (FLIPR). The assay was further used to detect the dose-effect relationships of tool compounds, the EC50 values of agonist GABA (137.42 ± 26.31 nM), positive allosteric modulator diazepam (3.22 ± 0.73 μM), and antagonist gabazine (0.16 ± 0.04 μM), blocking agents bicuculine (0.47 ± 0.06 μM) and PTX (6.39 ± 1.17 μM). In the meanwhile, the compounds were screened from a compound library (10000) by the membrane potential dye assay. Selected 4 active compounds were further identified for their EC50 values in vitro by electrophysiological method, the EC50 values of 4 compounds were further determined as 1.37 ± 0.43 μM, 0.69 ± 0.17 μM, 0.77 ± 0.16 μM, and 1.62 ± 0.29 μM. Furthermore, the pentobarbital sleep rate and the sleep time of mice pretreated with 4 active compounds by oral administration were significantly increased compared with mice pretreated with a negative control in vivo experiment. Conclusion: We successfully generated a stable CHO cell line expressing human GABAA1 by induced expression strategy which decreased cytotoxicity. Then, developed an efficient membrane potential detection method for high-throughput screening, the assay based on the stable cell line could distinguish different types of GABAA1 modulators, which would be an effective in vitro system to screen the GABAAR-targeted compounds. Compared with the patch clamp electrophysiological detection method, the membrane potential detection method has higher detection flux for compounds and higher detection sensitivity for active compounds.

Purpose: Minichromosome maintenance (MCM) has been demonstrated to be involved in tumorigenesis and pathogenesis of many cancer types. However, the role of MCMs in endometrial cancer (EC) has not been elucidated. Materials and Methods: We first employed GEPIA, cBioPortal, and R software to perform the differential expression analysis, survival analysis, and gene alteration analysis of the MCMs family. Then, GSE17025 and GSE63678 datasets and CTPAC were used to verify the mRNA and protein expression levels of MCM4. In addition, the internal mechanism of the MCM4 was investigated by comparing MCM4 expression-correlated differentially expressed genes (DEGs) from GEPIA and MCM4-interacted genes from STRING. Last, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to identify MCM4-related biological processes. Results: Compared with normal tissues, only MCM2 and MCM4 expression were significantly upregulated in EC tissues. High expression of MCM4 was related to worse clinicopathological features and poor prognosis in EC cohorts. Additionally, a certain degree of gene alterations in the MCM2-7 gene was observed. By comparing MCM4 expression-correlated DEGs and MCM4- interacted genes, six genes were obtained: SSRP1, ORC1, GINS1, CDK2, DBF4 and GINS3. Functional enrichment analysis suggested that MCM4 may be involved in regulating the biological processes of DNA replication and the p53 signaling pathway. Conclusion: This was the first comprehensive study to disclose the biological effects of MCMs in EC, indicating that MCM4 could be used as a new prognostic biomarker and potential therapeutic target for EC.

Objectives: To explore the inhibitory effect of verapamil, a calcium channel blocker, on the growth of human airway granulation fibroblasts to provide an experimental basis for the clinical use of calcium channel blockers in preventing and treating benign airway stenosis. Methods: Primary human airway normal fibroblasts and human airway granulation fibroblasts were cultured by tissue block attachment culture method, and the experimental studies were carried out using 3-8 generation cells. Cell Counting Kit-8 (CCK-8) was used to test the proliferation of human normal airway fibroblasts and human airway granulation fibroblasts and the semi-inhibitory concentration of verapamil on normal airway fibroblasts and airway granulation fibroblasts. A scratch test detected the migration effect of verapamil on human airway granulation fibroblasts. The mRNA relative expression levels of related factors were detected by PCR to compare the differences between normal airway fibroblasts and airway granulation fibroblasts. Western blot was used to detect the relative amount of related proteins and compare the differences between normal airway fibroblasts and granulation airway fibroblasts. After 48 hours of treatment with half of the inhibitory concentration of Vera Pammy for granulation airway fibroblasts, the relative expression levels of related factors on mRNA and protein were observed. Results: Human normal airway fibroblasts and human airway granulation fibroblasts with a purity of more than 95% could be obtained from primary culture by tissue block adherence method. CCK8 results showed that the proliferation rate of human airway granulation fibroblasts was faster than that of the normal human airway fibroblasts. The semi-inhibitory concentration of verapamil on human normal airway fibroblasts was 92.81 ug/ml, while the semi-inhibitory concentration on human airway granulation fibroblasts was 69.57 ug/ml. The scratch test indicated that the cell migration rate of human airway granulation fibroblasts treated with verapamil decreased significantly (P < 0.05). PCR results showed that the mRNA relative expression levels of TGFβ1, COL1A1, Smad2/3, VEGFA, IL6, and IL8 in human airway granulation fibroblasts were significantly higher than those in normal human airway fibroblasts (P < 0.05). The mRNA relative expressions of TGFβ1, smad2/3, and COL1A1 in human airway granulation fibroblasts treated with semi-inhibited verapamil for 48h were down-regulated (P < 0.05), while the mRNA relative expressions of VEGFA, IL6 and IL8 had no significant changes (P > 0.05). WB test showed that the relative protein expressions of TGFβ1, Smad2, and VEGFC in human airway granulation fibroblasts were upregulated (P < 0.05) but downregulated after verapamil treatment compared with before treatment (P < 0.05). Conclusion: Calcium channel blockers can inhibit the proliferation of human airway granulation fibroblasts through TGFβ1/ Smad pathway, which may be a method to prevent and treat benign airway stenosis.

Aim: In this study, we aimed to investigate whether resveratrol has anti-inflammatory effects on LPS-induced ALI via TTP enhancement. Background: Acute lung injury (ALI) is a syndrome of diffuse infammatory lung injury with increased pulmonary edema and the rapid onset of hypoxemic respiratory failure. Resveratrol is a stilbenoid, a form of natural phenol, and a phytoalexin produced by a variety of plants in reaction to injury or when they are attacked by pathogens like bacteria or fungi. Resveratrol exhibits a potent antiinflammatory effect in LPS-induced ALI, while the underlying mechanisms remain elusive. Objective: Tristetraprolin (TTP) is a RNA binding protein that is an important endogenous inhibitor of inflammation. The objective of the present study is to investigate whether resveratrol has anti- inflammatory effects on LPS-induced ALI via TTP enhancement. Methods: Forty male C57BL/6 mice were randomly assigned to four groups and intratracheally instilled with 5 mg/kg lipopolysaccharide (LPS) to induce ALI. Results: LPS-induced lung pathological damage, lung edema, and neutrophil infiltration were reduced by resveratrol pretreatment. Furthermore, resveratrol inhibited the LPS-induced rise in TNF- α, IL-1β and IL-6 levels in BAL fluids. In the LPS-challenged mouse's lung tissue, resveratrol clearly boosted sirtuin1 (SIRT1) and TTP protein expression, while also increasing TTP expression while reducing proinflammatory cytokines. EX527, on the other hand, reversed resveratrol's effects. Conclusion: According to our findings, resveratrol attenuated pulmonary inflammation and lung injury in mice with LPS-induced ALI#140; at least partly correlated with promoting the activation of SIRT1/TTP signaling pathway, highlighting these pathways as potential targets for intervention in LPS -induced lung injury.

Background: Dendrobium officinalis Six nostrum (DOS) can be prepared by adding Dendrobium officinalis into Simiao Wan in accordance with the Traditional Chinese Medicine (TCM) theory and other previous findings. Our previous study has shown that DOS treatment can lead to a marked decrease in Serum UA (SUA) levels. The purpose of this study was to explore the effects of DOS on intestinal UA excretion in hyperuricemia and its underlying mechanisms. Methods: DOS was administered intragastrically to hyperuricemic rats induced by oral administration of HX and PO for 7 weeks. The SUA level, fecal UA and XOD activity were detected. The expressions of UA transporters (ABCG2, GLUT9, and PDZK1), CNT2, and tight junction proteins (ZO- 1 and claudin-1) in the intestine were assayed by IHC staining. The serum LPS and DAO levels were detected by ELISA kits. The intestinal histological changes were assessed using H staining. Results: DOS treatment decreased the SUA level while markedly increasing the fecal UA level by 28.85%~35.72%. Moreover, DOS effectively up-regulated the expression of ABCG2 and PDZK1 and down-regulated the expression of GLUT9 in the intestine. DOS markedly decreased the serum LPS level by 21.4%~32.1% and DAO activity by 12.3%~19.7%, which in turn ameliorated the intestinal pathology. As a result, it could protect intestinal barrier function, as indicated by the increase of villus height (V), the reduction of the crypt depth (C), and the elevation of the V/C ratio. It also increased the expression of ZO-1 and claudin-1. In addition, DOS significantly down-regulated the expression of CNT2, which reduced purine nucleoside transportation from the intestine into the blood, and inhibited XOD activity, leading to a decrease in UA production. Conclusion: DOS exerted anti-hyperuricemic effects via regulation of intestinal urate transporters and could protect intestinal barrier function by restoring the expressions of ZO-1 and claudin-1.