Dizajniranje sustava isporuke 5-fluorouracila u kolon tabletama obloženima miješanim filmom

The study was carried out to establish the effectiveness of a mixed film composed of ethyl cellulose/Eudragit S100 for colonic delivery of 5-flourouracil (5-FU). Tablets cores containing 5-FU were prepared by direct compression method by coating at different levels (2–9 %, m/m) with a non-aqueous solution containing ethylcellulose/Eudragit S100. Coated tablets were studied for the in vitro release of 5-FU and the samples were analyzed spectrophotometrically at 266 nm. Drug release from coated systems depended on the thickness of the mixed film and the composition of the core. Channel formation was initiated in the coat by dissolution of the Eudragit S 100 fraction at higher pH in the colonic region. The release was found to be higher in tablets containing Avicel as filler owing to its wicking action compared to that from lactose containing cores. Furthermore, batches containing superdisintegrant (1 %, m/m Cross-PVP) along with Avicel in the core released approximately 81.1 % drug during the colonic transit time. Kinetic studies indicated that all the formulations followed first-order release kinetics. The developed delivery system will expectedly deliver the drug to the colon.Cilj rada bio je pripraviti miješane filmove od etilceluloze i Eudragita S100 za isporuku 5-flourouracil (5-FU) u kolon. Jezgre tableta s 5-FU pripravljene su metodom izravne kompresije koristeći nevodenu otopinu etilceluloze/Eudragita S100 (2–9 %, m/m). Iz obloženih tableta proučavano je in vitro oslobađanje 5-FU koristeći speckrofotometrijsku analizu na 266 nm. Oslobađanje lijeka iz obloženog sustava ovisilo je o debljini filma i sastavu jezgre tablete. Stvaranje kanala u ovojnici potaknuto je otapanjem frakcije s Eudragitom S 100 pri višim pH u debelom crijevu. Jače oslobađanje bilo je iz tableta s Avicelom kao punilom nego iz tableta s laktozom zahvaljujući kapilarnom djelovanju Avicela. Nadalje, pripravci sa superdezintegratorom (1 %, m/m Cross-PVP) i Avicelom oslobađali su približno 81,1 % lijeka u vremenu koje je potrebno za prolaz tableta kroz kolon. Kinetička ispitivanja pokazuju da svi pripravci slijede kinetiku prvog reda. Razvijeni sustavi trebali bi biti pogodni za isporuku lijeka u kolon

Exploring Subpixel Learning Algorithms for Estimating Global Land Cover Fractions from Satellite Data Using High Performance Computing

Land cover (LC) refers to the physical and biological cover present over the Earth’s surface in terms of the natural environment such as vegetation, water, bare soil, etc. Most LC features occur at finer spatial scales compared to the resolution of primary remote sensing satellites. Therefore, observed data are a mixture of spectral signatures of two or more LC features resulting in mixed pixels. One solution to the mixed pixel problem is the use of subpixel learning algorithms to disintegrate the pixel spectrum into its constituent spectra. Despite the popularity and existing research conducted on the topic, the most appropriate approach is still under debate. As an attempt to address this question, we compared the performance of several subpixel learning algorithms based on least squares, sparse regression, signal–subspace and geometrical methods. Analysis of the results obtained through computer-simulated and Landsat data indicated that fully constrained least squares (FCLS) outperformed the other techniques. Further, FCLS was used to unmix global Web-Enabled Landsat Data to obtain abundances of substrate (S), vegetation (V) and dark object (D) classes. Due to the sheer nature of data and computational needs, we leveraged the NASA Earth Exchange (NEX) high-performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into four classes, namely forest, farmland, water and urban areas (in conjunction with nighttime lights data) over California, USA using a random forest classifier. Validation of these LC maps with the National Land Cover Database 2011 products and North American Forest Dynamics static forest map shows a 6% improvement in unmixing-based classification relative to per-pixel classification. As such, abundance maps continue to offer a useful alternative to high-spatial-resolution classified maps for forest inventory analysis, multi-class mapping, multi-temporal trend analysis, etc