Ursolic Acid Ameliorates the Injury of H9c2 Cells Caused by Hypoxia and Reoxygenation Through Mediating CXCL2/NF-κB Pathway.

Ursolic acid (UA) has been reported to possess several biological benefits, such as anti-cancer, anti-inflammation, antibacterial, and neuroprotective functions. This study detects the function and molecular mechanism of UA in H9c2 cells under hypoxia and reoxygenation (H/R) conditions.Under H/R stimulation, the effects of UA on H9c2 cells were examined using ELISA and western blot assays. The Comparative Toxicogenomics Database was employed to analyze the target molecule of UA. Small interfering RNA was used to knock down CXCL2 expression, further exploring the function of CXCL2 in H/R-induced H9c2 cells. The genes related to the nuclear factor-kappa B (NF-κB) pathway were assessed using western blot analysis.Significant effects of UA on H/R-induced H9c2 cell damage were observed, accompanied by reduced inflammation and oxidative stress injury. Additionally, the increased level of CXCL2 in H/R-induced H9c2 cells was reduced after UA stimulation. Moreover, CXCL2 knockdown strengthened the beneficial effect of UA on H/R-induced H9c2 cells. HY-18739, an activator of the NF-κB pathway, can increase CXCL2 expression. Moreover, the increased levels of p-P65 NF-κB and p-IκBα in H/R-induced H9c2 cells were remarkably attenuated by UA treatment.In summary, the results indicated that UA may alleviate the damage of H9c2 cells by targeting the CXCL2/NF-κB pathway under H/R conditions.

Ursolic acid protects against anoxic injury in cardiac microvascular endothelial cells by regulating intercellular adhesion molecule-1 and toll-like receptor 4/MyD88/NF-κB pathway.

BACKGROUND: Cardiac microvascular endothelial cells (CMECs) are rapidly damaged after myocardial ischemia or hypoxia. In this study, we intend to explore whether ursolic acid (UA) can protect CMECs against hypoxia/reoxygenation (H/R) injury and to detect related molecular mechanism. METHODS: CMECs were subjected to H/R condition in the absence or presence of UA. Cell behaviors were measured by Cell Counting Kit-8, transwell, ELISA and western blot assays. siRNA was applied to reduce ICAM1 expression, then the effect of co-treatment of UA and si-ICAM1 on CMECs has been detected by biological experiments. RESULTS: Under H/R stimulation, the proliferation and migration of CMECs were inhibited, as well as the inflammation and oxidative stress were enhanced. UA treatment obviously reversed these H/R-induced injuries and reduced ICAM1 expression. Moreover, knockdown of ICAM1 could alleviate the H/R-induced injuries and strengthen the protective effect of UA on CMECs under H/R condition. Additionally, the protein levels of TLR4, MyD88 and p-P65 NF-κB were obviously increased after H/R stimulation, whereas the addition of UA could alter the phenomena by reducing TLR4, MyD88, and p-P65 NF-κB expression. CONCLUSIONS: Our results insinuated that UA could alleviate H/R-induced injuries in CMECs by regulating ICAM1 and TLR4/MyD88/NF-κB pathway.

Effects of Ligustrazine on Airway Inflammation in A Mouse Model of Neutrophilic Asthma.

OBJECTIVE: To investigate the effects of ligustrazine (LTZ) on airway inflammation in a mouse model of neutrophilic asthma (NA). METHODS: Forty healthy C57BL/6 female mice were randomly divided into 4 groups using a random number table, including the normal control, NA, LTZ and dexamethasone (DXM) groups, with 10 rats in each group. The NA mice model was established by the method of ovalbumin combined with lipopolysaccharide sensitization. At 0.5 h before each challenge, LTZ and DXM groups were intraperitoneally injected with LTZ (80 mg/kg) or DXM (0.5 mg/kg) for 14 d, respectively, while the other two groups were given the equal volume of normal saline. After last challenge for 24 h, the aerosol inhalation of methacholine was performed and the airway reactivity was measured. The bronchoalveolar lavage fluid (BALF) was collected. The Wright-Giemsa staining was used for total white blood cells and differential counts. The levels of cytokines interleukin (IL)-17 and IL-10 were detected by enzyme-linked immunosorbent assay. The pathological change of lung tissue was observed by hematoxylin eosin staining. RESULTS: The airway responsiveness of the NA group was signifificantly higher than the normal control group (P<0.05), while those in the LTZ and DXM groups were signifificantly lower than the NA group (P<0.05). The neutrophil and eosinophil counts in the LTZ and DXM groups were signifificantly lower than the NA group (P<0.05), and those in the LTZ group were signifificantly lower than the DXM group (P<0.05). There were a large number of peribronchiolar and perivascular inflammatory cells in fifiltration in the NA group. The airway inflflammation in the LTZ and DXM groups were signifificantly alleviated than the NA group. The infifiltration in the LTZ group was signifificantly reduced than the DXM group. Compared with the normal control group, the IL-17 level in BALF was signifificantly increased and the IL-10 level in BALF was signifificantly decreased in the NA group (P<0.05). LTZ and DXM treatment signifificantly decreased IL-17 levels and increased IL-10 levels compared with the NA group (P<0.05), and the changes in the above indices were more signifificant in the LTZ group (P<0.05). CONCLUSION: LTZ could alleviate the airway inflflammation in the NA mice model through increasing the IL-10 level and decreasing the IL-17 level.

Microarray and network-based identification of functional modules and pathways of active tuberculosis.

Diagnose of active tuberculosis (TB) is challenging and treatment response is also difficult to efficiently monitor. The aim of this study was to use an integrated analysis of microarray and network-based method to the samples from publically available datasets to obtain a diagnostic module set and pathways in active TB. Towards this goal, background protein-protein interactions (PPI) network was generated based on global PPI information and gene expression data, following by identification of differential expression network (DEN) from the background PPI network. Then, ego genes were extracted according to the degree features in DEN. Next, module collection was conducted by ego gene expansion based on EgoNet algorithm. After that, differential expression of modules between active TB and controls was evaluated using random permutation test. Finally, biological significance of differential modules was detected by pathways enrichment analysis based on Reactome database, and Fisher's exact test was implemented to extract differential pathways for active TB. Totally, 47 ego genes and 47 candidate modules were identified from the DEN. By setting the cutoff-criteria of gene size >5 and classification accuracy ≥0.9, 7 ego modules (Module 4, Module 7, Module 9, Module 19, Module 25, Module 38 and Module 43) were extracted, and all of them had the statistical significance between active TB and controls. Then, Fisher's exact test was conducted to capture differential pathways for active TB. Interestingly, genes in Module 4, Module 25, Module 38, and Module 43 were enriched in the same pathway, formation of a pool of free 40S subunits. Significant pathway for Module 7 and Module 9 was eukaryotic translation termination, and for Module 19 was nonsense mediated decay enhanced by the exon junction complex (EJC). Accordingly, differential modules and pathways might be potential biomarkers for treating active TB, and provide valuable clues for better understanding of molecular mechanism of active TB.