In vitro Evaluation of Novel Sustained Release Microspheres of Glipizide Prepared by the Emulsion Solvent Diffusion-Evaporation Method

The objective of the current investigation is to reduce dosing frequency and improve patient compliance by designing and systematically evaluating sustained release microspheres of Glipizide. An anti-diabetic drug, Glipizide, is delivered through the microparticulate system using ethyl cellulose as the controlled release polymer. Microspheres were developed by the emulsion solvent diffusion-evaporation technique by using the modified ethanol,-dichloromethane co-solvent system. The polymer mixture of ethyl cellulose and Eudragit® S100 was used in different ratios (1:0, 1:1, 2:3, 1:4 and 0:1) to formulate batches F1 to F5. The resulting microspheres were evaluated for particle size, densities, flow properties, morphology, recovery yield, drug content, and in vitro drug release behavior. The formulated microspheres were discrete, spherical with relatively smooth surface, and with good flow properties. Among different formulations, the fabricated microspheres of batch F3 had shown the optimum percent drug encapsulation of microspheres and the sustained release of the Glipizide for about 12 h. Release pattern of Glipizide from microspheres of batch F3 followed Korsmeyers-peppas model and zero-order release kinetic model. The value of ‘n’ was found to be 0.960, which indicates that the drug release was followed by anomalous (non-fickian) diffusion. The data obtained thus suggest that a microparticulate system can be successfully designed for sustained delivery of Glipizide and to improve dosage form characteristics for easy formulation

Weighted Fisher Discriminant Analysis in the Input and Feature Spaces

Fisher Discriminant Analysis (FDA) is a subspace learning method which minimizes and maximizes the intra- and inter-class scatters of data, respectively. Although, in FDA, all the pairs of classes are treated the same way, some classes are closer than the others. Weighted FDA assigns weights to the pairs of classes to address this shortcoming of FDA. In this paper, we propose a cosine-weighted FDA as well as an automatically weighted FDA in which weights are found automatically. We also propose a weighted FDA in the feature space to establish a weighted kernel FDA for both existing and newly proposed weights. Our experiments on the ORL face recognition dataset show the effectiveness of the proposed weighting schemes.Comment: Accepted (to appear) in International Conference on Image Analysis and Recognition (ICIAR) 2020, Springe

Sleep deprivation in depression

Ten patients diagnosed as suffering from depressive illness were treated with 2 consecutive nights of sleep deprivation. Sleep deprivation was effective in both types of depression viz. endoge-nous and reactive. The improvement was greater and seemed to last longer in endogenous depression as compared to reactive depression at the time of evaluation, 7 days after completion of sleep deprivation. Depressed mood, suicidal tendencies and retard-ation seemed to show the greatest improvement while insight and gastro-intestinal and somatic symptoms, improved the least