Hyaluronic acid receptor CD44 deficiency is associated with decreased Cryptococcus neoformans brain infection

Cryptococcus neoformans is a pathogenic yeast that can invade the brain and cause meningoencephalitis. Our previous in vitro studies suggested that the interaction between C. neoformans hyaluronic acid and human brain endothelial CD44 could be the initial step of brain invasion. In this report, we used a CD44 knock-out (KO or CD44(-/-)) mouse model to explore the importance of CD44 in C. neoformans brain invasion. Our results showed that C. neoformans-infected CD44 KO mice survived longer than the infected wild-type mice. Consistent with our in vitro results, the brain and cerebrospinal fluid fungal burden was reduced in CD44-deficient mice. Histopathological studies showed smaller and fewer cystic lesions in the brains of CD44 KO mice. Interestingly, the cystic lesions contained C. neoformans cells embedded within their polysaccharide capsule and were surrounded by host glial cells. We also found that a secondary hyaluronic acid receptor, RHAMM (receptor of hyaluronan-mediated motility), was present in the CD44 KO mice. Importantly, our studies demonstrated an in vivo blocking effect of simvastatin. These results suggest that the CD44 and RHAMM receptors function on membrane lipid rafts during invasion and that simvastatin may have a potential therapeutic role in C. neoformans infections of the brain.     

Detecting and cleaning outliers for robust estimation of variogram models in insect count data

Outlier detection and cleaning procedures were evaluated to estimate mathematical restricted variogram models with discrete insect population count data. Because variogram modeling is significantly affected by outliers, methods to detect and clean outliers from data sets are critical for proper variogram modeling. In this study, we examined spatial data in the form of discrete measurements of insect counts on a rectangular grid. Two well-known insect pest population data were analyzed; one data set was the western flower thrips, Frankliniella occidentalis (Pergande) on greenhouse cucumbers and the other was the greenhouse whitefly, Trialeurodes vaporariorum (Westwood) on greenhouse cherry tomatoes. A spatial additive outlier model was constructed to detect outliers in both the isolated and patchy spatial distributions of outliers, and the outliers were cleaned with the neighboring median cleaner. To analyze the effect of outliers, we compared the relative nugget effects of data cleaned of outliers and data still containing outliers after transformation. In addition, the correlation coefficients between the actual and predicted values were compared using the leave-one-out cross-validation method with data cleaned of outliers and non-cleaned data after unbiased back transformation. The outlier detection and cleaning procedure improved geostatistical analysis, particularly by reducing the nugget effect, which greatly impacts the prediction variance of kriging. Consequently, the outlier detection and cleaning procedures used here improved the results of geostatistical analysis with highly skewed and extremely fluctuating data, such as insect counts.     

Accumulation of galloyl derivatives in a green alga, Spirogyra varians, in response to cold stress

The green alga Spirogyra varians accumulated antioxidative compounds in response to cold stress. When the algae were transferred from 20°C to 4°C, the amount of phenolic contents and flavonoids in the cell increased 17 times and 30 times, respectively, in 2 months. At this time, the radical scavenging activity of the methanolic extract of S. varians was 238 times higher than that of initial culture. To identify the responsible antioxidants, the methanolic extract was obtained from the algae grown at 4°C. HPLC analysis of the extract showed six compounds newly produced or increased over time. Four of the compounds were successfully purified, and the structures were identified using ¹H NMR spectroscopy. The compounds were galloyl derivatives—methyl gallate, 1-O-Galloyl-β-d-glucose, 1,2,3,6-tetra-O-Galloyl-β-d-glucose and 1,2,3,4,6-penta-O-Galloyl-β-d-glucose which are intermediates of the shikimate pathway.     

Modulation of FoxO1 phosphorylation/acetylation by baicalin during aging

Baicalin is a flavonoid known to modify various redox-related biological activities. Included is its ability to suppress reactive species (RS) producing activity and modulate nuclear factor-κB through cellular redox regulation with enhanced thiol ability. FoxO regulates various genes that are known to be involved in cellular metabolism related to cell death and the oxidative stress response. One such case is the prevention of FoxO1 expression by activated insulin-induced phosphatidylinositol 3-kinase (PI3K)/Akt, which leads to increased oxidative stress and aging processes. In the present study, we attempted to elucidate the molecular modulation of antioxidant baicalin on the insulin-induced FoxO1 inactivation. We used HEK293T cultured cells and kidney tissue isolated from 24-month-old rats treated with baicalin at a dose of 10 or 20 mg/kg/day for 10 days. We found that baicalin enhanced catalase and suppressed RS production in cell system and in isolated kidney tissue in contrast to the nontreated aged rats. Results also showed activation of insulin signaling (PI3K/Akt), FoxO1 phosphorylation/acetylation and the down-regulation of catalase and manganese superoxide dismutase, both of which are FoxO1-targeting genes. Furthermore, baicalin-treated rats showed a decreased FoxO1 phosphorylation via PI3K/Akt cascade and FoxO1 acetylation by the cAMP-response element-binding protein binding protein (CBP). These results strongly suggest that treatment with baicalin influenced phosphorylation/acetylation of FoxO1 by up-regulating PI3K/Akt signaling through insulin in aged rats. Our results further reveal that baicalin regulated FoxO1 phosphorylation via PI3K/Akt by insulin and FoxO1 acetylation by the interaction of CBP and SIRT1, leading to changes in catalase gene expression during aging.     

Dipeptidyl peptidase-4 inhibitor with β-amino amide scaffold: Synthesis, SAR and biological evaluation

Inhibitors of dipeptidyl peptidase-4 (DPP4) have been shown to be effective treatments for type 2 diabetes. Several series of β-amino amide containing piperazine derivatives have been prepared and evaluated as a inhibitor of DPP4. Finally compound 5m was selected for further evaluation.