Curcumin solid dispersion based on three model acrylic polymers: formulation and release properties

Abstract To investigate structure-property relationship of polymer-based curcumin solid dispersion (SD), three acrylic polymers were used to formulate curcumin SD by solvent evaporation method. Curcumin Eudragit EPO SD (cur@EPO), curcumin Eudragit RS PO SD (cur@RSPO) and curcumin Eudragit RL PO SD (cur@RLPO) showed deep red, golden orange and reddish orange color, respectively. Cur@RSPO entrapped 15.42 wt% of curcumin followed by cur@RL PO and cur@EPO. FTIR spectra indicated that in cur@EPO, curcumin may transfer hydrogen to the dimethylaminoethyl methacrylate group and thus change its color to red. In contrast, curcumin may form hydrogen bonding with Eudragit RS PO and Eudragit RL. Curcumin exists in amorphous state in three SDs as proved by differential scanning calorimetry and X-Ray diffraction measurement. In vitro digestion presented that lower pH value in simulated gastric fluid (SGF) stimulates the curcumin release from cur@EPO while permeability influences the release profile in other two SDs. When in simulated intestinal fluid (SIF), first order release model governs the release behaviors of all three SDs which showed sustained release pattern. Our results are helpful to elucidate how structure of polymer may impact on the major properties of curcumin contained SD and will be promising to broaden its therapeutic applications.

Groundwater Quality: Analysis of Its Temporal and Spatial Variability in a Karst Aquifer.

This study develops an approach based on hierarchical cluster analysis for investigating the spatial and temporal variation of water quality governing processes. The water quality data used in this study were collected in the karst aquifer of Yucatan, Mexico, the only source of drinking water for a population of nearly two million people. Hierarchical cluster analysis was applied to the quality data of all the sampling periods lumped together. This was motivated by the observation that, if water quality does not vary significantly in time, two samples from the same sampling site will belong to the same cluster. The resulting distribution maps of clusters and box-plots of the major chemical components reveal the spatial and temporal variability of groundwater quality. Principal component analysis was used to verify the results of cluster analysis and to derive the variables that explained most of the variation of the groundwater quality data. Results of this work increase the knowledge about how precipitation and human contamination impact groundwater quality in Yucatan. Spatial variability of groundwater quality in the study area is caused by: a) seawater intrusion and groundwater rich in sulfates at the west and in the coast, b) water rock interactions and the average annual precipitation at the middle and east zones respectively, and c) human contamination present in two localized zones. Changes in the amount and distribution of precipitation cause temporal variation by diluting groundwater in the aquifer. This approach allows to analyze the variation of groundwater quality controlling processes efficiently and simultaneously.

Practical Use of Computationally Frugal Model Analysis Methods.

Three challenges compromise the utility of mathematical models of groundwater and other environmental systems: (1) a dizzying array of model analysis methods and metrics make it difficult to compare evaluations of model adequacy, sensitivity, and uncertainty; (2) the high computational demands of many popular model analysis methods (requiring 1000's, 10,000 s, or more model runs) make them difficult to apply to complex models; and (3) many models are plagued by unrealistic nonlinearities arising from the numerical model formulation and implementation. This study proposes a strategy to address these challenges through a careful combination of model analysis and implementation methods. In this strategy, computationally frugal model analysis methods (often requiring a few dozen parallelizable model runs) play a major role, and computationally demanding methods are used for problems where (relatively) inexpensive diagnostics suggest the frugal methods are unreliable. We also argue in favor of detecting and, where possible, eliminating unrealistic model nonlinearities-this increases the realism of the model itself and facilitates the application of frugal methods. Literature examples are used to demonstrate the use of frugal methods and associated diagnostics. We suggest that the strategy proposed in this paper would allow the environmental sciences community to achieve greater transparency and falsifiability of environmental models, and obtain greater scientific insight from ongoing and future modeling efforts.