ABSTRACT
Objective To study the changes in morphology , phenotypes and gene expression pro-files of dendritic cells (DCs) following treatment with Seabuckthorn flavones (SF).Methods DCs were treated with 200μg/ml of SF and then cultured for 7 days.Changes in the morphology of DCs were observed under light microscope .Flow cytometry was used to detect DC surface molecules .Total RNA was extracted to construct the library for digital gene expression profiling ( DGE ) .Differentially expressed genes were screened out and further analyzed by gene ontology ( GO) enrichment analysis and Kyoto encyclopedia of genes and genomes ( KEGG ) pathway enrichment analysis .Results Compared with control group , SF treatment significantly enhanced the expression of HLA-DR, CD80, CD83 and CD86 on DCs.A total of 355 differentially expressed genes were screened out by DGE , including 176 up-regulated genes and 179 down-regulated genes .GO enrichment was mainly involved in the regulation and development of the immune sys -tem and other biological processes .KEGG pathway analysis showed that the significantly enriched pathways were closely related to inflammation , the immune system, cancer and other diseases .Conclusion SF can promote the expression of DC co-stimulatory molecules and pro-mature molecules, and regulate the expres-sion of immunity-related genes such as CD11a, SLAMF6, LMCD1, TSC22D3 and IKZF3.
ABSTRACT
The kinetics and mechanism of depolymerisation of solid sodium hyaluronate at elevated temperatures and various pH have been investigated. Depolymerisation was found to be governed by random chain scission. The activation energy at neutral pH was found to be 127 kJ/mol. The solid polymer was most stable at neutral pH. Results suggest the depolymerisation mechanism in solid- and solution state to be the same. Correlation of log intrinsic viscosity to log weight-average molecular weight was investigated to ensure high quality data for polymer size. Based on more than sixty hyaluronate samples spanning from 0.4 to 2.3 MDa, it was concluded that a second order polynomial regression gives a better fit than the linear regression offered by classical Mark-Houwink-Kuhn-Sakurada description. This finding was supported by literature data and could be expanded to other simple, well behaving linear polymers, such as polystyrene and polyethylene.
