AIM OF THE STUDY: This study is designed to investigate the vasorelaxation effect of G. uralensis from various extracts and to study its pharmacology effect.
MATERIALS AND METHODS: The vasorelaxation effect of G. uralensis extracts were evaluated on thoracic aortic rings isolated from Sprague Dawley rats.
RESULTS: Among these three extracts of G. uralensis, 50% ethanolic extract (EFG) showed the strongest vasorelaxation activity. EFG caused the relaxation of the aortic rings pre-contracted with phenylephrine either in the presence or absence of endothelium and pre-contracted with potassium chloride in endothelium-intact aortic ring. Nω-nitro-L-arginine methyl ester, methylene blue, or 1H-[1,2,4]Oxadiazolo[4,3-a]quinoxalin-1-one inhibit the vasorelaxation effect of EFG in the presence of endothelium. On the other hand, in the presence of the potassium channel blockers (tetraethylammonium and barium chloride), the vasorelaxation effect of EFG was not affected, but glibenclamide and 4-aminopyridine did inhibit the vasorelaxation effect of EFG. With indomethacin, atropine and propranolol, the vasorelaxation effect by EFG was significantly reduced. EFG was also found to be effective in reducing Ca(2+) release from sarcoplasmic reticulum and the blocking of calcium channels.
CONCLUSIONS: The results obtained suggest that EFG is involved in the NO/sGC/cGMP pathway.
METHODS: mRNA was extracted from 44 fibroadenomas and 36 giant fibroadenomas, and transcriptomic profiling was performed to identify up- and down-regulated genes in the giant fibroadenomas as compared to the fibroadenomas.
RESULTS: A total of 40 genes were significantly up-regulated and 18 genes were significantly down-regulated in the giant fibroadenomas as compared to the fibroadenomas of the breast. The top 5 up-regulated genes were FN1, IL3, CDC6, FGF8 and BMP8A. The top 5 down-regulated genes were TNR, CDKN2A, COL5A1, THBS4 and BMPR1B. The differentially expressed genes (DEGs) were found to be associated with 5 major canonical pathways involved in cell growth (PI3K-AKT, cell cycle regulation, WNT, and RAS signalling) and immune response (JAK-STAT signalling). Further analyses using 3 supervised learning algorithms identified an 8-gene signature (FN1, CDC6, IL23A, CCNA1, MCM4, FLT1, FGF22 and COL5A1) that could distinguish giant fibroadenomas from fibroadenomas with high predictive accuracy.
CONCLUSION: Our findings demonstrated that the giant fibroadenomas are biologically distinct to fibroadenomas of the breast with overexpression of genes involved in the regulation of cell growth and immune response.