Thermodynamic studies of naringenin-isonicotinamide cocrystals / 药学学报

The purpose of this study was to investigate the thermodynamics of naringenin (NAR)-isonicotinamide (INT) cocrystal (stoichiometric ratio, 1∶2) formed in different solvents. The dissolution behavior of cocrystal was explored in the water. Solubility of NAR-INT cocrystals under various temperatures were measured, followed by fitting the complexation model to calculate the thermodynamic parameters solubility products (Ksp), complexation constants (K12) and Gibbs energy change (ΔG) of cocrystal during formation progress. Ternary phase diagrams (TPDs) of the NAR-INT-solvent systems under various temperatures were plotted. Based on the non-linear simulation, 1∶2 complexation model was well fitted to the NAR-INT cocrystal formation in ethanol, isopropanol and ethyl acetate, while no complexation model was more suitable for that in methanol. The cocrystallization reaction was exothermic and spontaneous (ΔG H S Ksp increased while K12 decreased when increasing temperature, suggesting that the two components could cocrystallize more easily at the lower temperature. In comparison to TPDs in other solvents, the area of homogeneous liquid phase in ethyl acetate was the smallest, indicating the easiest formation of NAR-INT cocrystal in ethyl acetate. The current study provides a theoretical foundation for preparation and optimization of scale-up NAR-INT cocrystals.

A probability model for analyzing speckles in intravascular ultrasound images to facilitate image segmentation / 南方医科大学学报

Ultrasonic image speckles result from the interference of the reflected signals by the scatters in the detected tissue. The physical characteristics of the speckles are closely correlated with the structures of the biological tissues, and the probability distribution of these speckles differs across different tissues. Based on the probability characteristics of intravascular ultrasound (IVUS) speckles, a Gamma mixture model and Gaussian mixture model are proposed to describe the calcified plaque, soft plaque and normal vascular regions on IVUS images. Using KS test, KL divergence and correlation coefficient analysis, we found that the probability distributions of the speckles generated by calcified plaques and normal blood vessels were better described by the Gaussian mixture model, while the speckles caused by soft plaques were described better by the Gamma mixture model. Based on this finding, we propose a probability mixture model combining neighborhood information for plaque segmentation on IVUS images. Compared with the existing probabilistic mixture model, the segmentation accuracy was greatly improved with a reduced noise.