Physicochemical properties, antioxidant activities and α-glucosidase inhibitory effects of polysaccharides from Evodiae fructus extracted by different solvents.

In this study, polysaccharides from Evodiae fructus were extracted by water, 0.5 M HCl, 0.5 M NaOH, water + 0.5 M HCl and water + 0.5 M NaOH, which were named as ERP-W, ERP-AC, ERP-AK, ERP-W-AC and ERP-W-AK, respectively. Their physicochemical properties, antioxidant activities and α-glucosidase inhibitory effects were investigated and compared. Physico-chemical analysis showed that they were acidic heteropolysaccharides, which had α- and ß-configurations. ERP-W, ERP-AK and ERP-W-AK were mainly composed of Rha, Ara, Gal, Glc and Gal-UA, while ERP-AC and ERP-W-AC were dominantly made up of Rha, Gal and Gal-UA. ERP-AK had the highest yield (24.5%) and the best thermal stability, ERP-AC and ERP-W-AC showed better homogeneity and lower molecular weight (83.6 and 41.6 kDa), and ERP-W possessed the highest neutral sugar content (50.7%) and molecular weight. Biological evaluation indicated that ERP-W, ERP-AK and ERP-W-AK had relatively stronger antioxidant activities, including ABTS, DPPH, OH and O2- radicals scavenging activities, Fe2+ chelating ability and α-glucosidase inhibitory effects. Moreover, these actions were considerably related to their physicochemical properties especially monosaccharide composition and molecular weight. Therefore, polysaccharides extracted by water and alkaline solvents from Evodiae fructus could be developed as promising natural antioxidants and α-glucosidase inhibitors in the food and medicine industries.

A statistical study of the factors influencing the extent of respiratory motion blur in PET imaging.

Respiratory motion results in significant motion blur in thoracic and abdomen PET imaging. The extent of respiratory motion blur is mainly correlated with breathing amplitude, tumor size and location. In this paper we introduce a statistical study to quantitatively show the factors influencing the extent of respiratory motion blur in thoracic PET images. The study is centered on two regression models, one is linked with motion blur induced loss of mean intensity(LMI), tumor motion magnitude and tumor size, and another is to investigate the influence of tumor location, patient gender and patient height on tumor motion magnitude. We use the blur identification and image restoration technique to estimate the tumor motion and compute the LMI. The regression model was validated by simulation and phantom data before extended to 39 cases of clinical lung tumor PET images corrupted with blurring artifact. Results show that the motion magnitude of lung tumor during breathing is 10.9±3.7mm in transaxial plane, and it is significantly greater in lower lung lobes than in upper lobes. The LMI is 7.1±2.4% in the region of interest (ROI) above 40% of the image's maximum intensity. The least-square estimate of regression equations demonstrates that LMI is proportional to tumor motion magnitude and is inversely proportional to tumor size; the two factors play the same role in determining the extent of respiratory motion blur in thoraco-abdominal PET imaging. The location of tumor was shown as the major factor determining its motion magnitude, while the influencing of patient gender and height on tumor motion was not shown significant.

Respiratory motion blur identification and reduction in ungated thoracic PET imaging.

Respiratory motion results in significant motion blur in thoracic positron emission tomography (PET) imaging. Existing approaches to correct the blurring artifact involve acquiring the images in gated mode and using complicated reconstruction algorithms. In this paper, we propose a post-reconstruction framework to estimate respiratory motion and reduce the motion blur of PET images acquired in ungated mode. Our method includes two steps: one is to use minmax directional derivative analysis and local auto-correlation analysis to identify the two parameters blur direction and blur extent, respectively, and another is to employ WRL, à trous wavelet-denoising modified Richardson-Lucy (RL) deconvolution, to reduce the motion blur based on identified parameters. The mobile phantom data were first used to test the method before it was applied to 32 cases of clinical lung tumor PET data. Results showed that the blur extent of phantom images in different directions was accurately identified, and WRL can remove the majority of motion blur within ten iterations. The blur extent of clinical images was estimated to be 12.1 ± 3.7 mm in the direction of 74 ± 3° relative to the image horizontal axis. The quality of clinical images was significantly improved, both from visual inspection and quantitative evaluation after deconvolution. It was demonstrated that WRL outperforms RL and a Wiener filter in reducing the motion blur with one to two more iterations. The proposed method is easy to implement and thus could be a useful tool to reduce the effect of respiration in ungated thoracic PET imaging.

Bicyclic cyanothiazolidines as novel dipeptidyl peptidase 4 inhibitors.

The synthesis and biochemical evaluation of novel cyanothiazolidine inhibitors of dipeptidyl peptidase 4 (DPP4) is described. Their main structural feature is a constrained bicyclic core that prevents the intramolecular formation of inactive cyclic species. The inhibitors show good to moderate biochemical potency against DPP4 and display distinct selectivity profiles towards DPP7, DPP8 and DPP9 depending on their substitution.