Biomedical subjects
Publications and source records attributed to M S Noh.
A series of 2,2-dimethyl-5-[4-(methylsulfonyl)phenyl]-4-phenyl-3(2H)furanones was prepared and evaluated for their ability to inhibit cyclo-oxygenase-2 (COX-2).
In order to delineate the mechanism involved in the anti-inflammatory activity of rutaecarpine, its effects on the production of prostaglandin (PG) and therein involved enzymes were examined. Rutaecarpine reduced the production of PGE(2) in RAW264.7 cells treated with lipopolysaccharide (LPS) in a dose dependent manner when added to the culture media at the time of stimulation. However, the inhibition of total cellular cyclooxygenase (COX) activity under the same experimental condition was observed only at high concentrations of rutaecarpine. Rutaecarpine did not affected the levels of COX-2 mRNA and protein in macrophages stimulated with LPS. Calcium ionophore A23187 induced-PG production and [(3)H]-arachidonic acid release were significantly decreased by the pretreatment of rutaecarpine for 30 minutes. With the same treatment schedule, however, rutaecarpine failed to alter the activities of cellular COX-1 and COX-2. Collectively, our data suggest that anti-inflammatory effect of rutaecarpine is, at least in part, ascribed to the diminution of PG production through inhibition of arachidonic acid release albeit the nature of its effects on PLA(2) activity remains to be elaborated.
The powerful general Pacala-Hassell host-parasitoid model for a patchy environment, which allows host density-dependent heterogeneity (HDD) to be distinguished from between-patch, host density-independent heterogeneity (HDI), is reformulated within the class of the generalized linear model (GLM) family. This improves accessibility through the provision of general software within well-known statistical systems, and allows a rich variety of models to be formulated. Covariates such as age class, host density and abiotic factors may be included easily. For the case where there is no HDI, the formulation is a simple GLM. When there is HDI in addition to HDD, the formulation is a hierarchical generalized linear model. Two forms of HDI model are considered, both with between-patch variability: one has binomial variation within patches and one has extra-binomial, overdispersed variation within patches. Examples are given demonstrating parameter estimation with standard errors, and hypothesis testing. For one example given, the extra-binomial component of the HDI heterogeneity in parasitism is itself shown to be strongly density dependent.