Florida Polytechnic University

About: Florida Polytechnic University is a education organization based out in Lakeland, Florida, United States. It is known for research contribution in the topics: Computer science & Catalysis. The organization has 302 authors who have published 538 publications receiving 6549 citations. The organization is also known as: Florida Poly.

Improved Pharmacodynamic Potential of Rosuvastatin by Self-Nanoemulsifying Drug Delivery System: An in vitro and in vivo Evaluation.

Abstract: Purpose The purpose of this proposed research was to investigate a nano-formulation developed using self-nanoemulsifying drug delivery system (SNEDDS) to improve the pharmacodynamic potential of rosuvastatin by assisting its transportation through lymphatic circulation. Methods The utilized lipids, surfactants, and co-surfactants for SNEDDS were selected on the basis of solubility studies. The SNEDDS formulation was optimized by implementing a D-optimal mixture design, wherein the effect of concentration of Capmul MCM EP (X1), Tween 20 (X2) and Transcutol P (X3) as independent variables was studied on droplet size (Y1), % cumulative drug release (Y2) and self-emulsification time (Y3) as dependent variables. The optimized formulation was evaluated via in vitro parameters and in vivo pharmacodynamic potential in Wistar rats. Results The D-optimal mixture design and subsequent ANOVA application resulted in the assortment of the optimized SNEDDS formulation that exhibited a droplet size of nano range (14.91nm), in vitro drug release of >90% within 30 minutes, and self-emulsification time of 16 seconds. The in vivo pharmacodynamic study carried out using Wistar rats confirmed the better antihyperlipidemic potential of developed formulation in normalizing the lipidic level of serum in contrast to pure drug and marketed tablets. Conclusion This research reports the application of D-optimal mixture design for successful and systematic development of rosuvastatin-loaded SNEDDS with distinctly enhanced in vitro and in vivo performance in comparison to marketed formulation. Eventually, improved anti-hyperlipidemic efficacy was envisaged which might be attributed to increased drug solubility and absorption. Overall, this study shows the utility of SNEDDS for improving the dissolution rate and bioavailability of poor aqueous-soluble drugs. The present SNEDDS formulation could be a promising approach and alternative to conventional dosage form.

A flower-like ZnO–Ag2O nanocomposite for label and mediator free direct sensing of dinitrotoluene

Abstract: 2,4-Dinitrotoluene (2,4-DNT) is a nitro aromatic compound used as a raw material for trinitrotoluene (TNT) explosive synthesis along with several other industrial applications. Easy, rapid, cost-effective, and selective detection of 2,4-DNT is becoming essential due to its hepato carcinogenic nature and presence in surface as well as ground water as a contaminant. Keeping this in view, this research, for the first-time, reports the synthesis of novel ZnO–Ag2O composite nanoflowers on a gold (Au) substrate, to fabricate an electrochemical sensor for label-free, direct sensing of 2,4-DNT selectively. The proposed ZnO–Ag2O/Au sensor exhibits a sensitivity of 5 μA μM−1 cm−2 with a low limit of detection (LOD) of 13 nM, in a linear dynamic range (LDR) of 0.4 μM to 40 μM. The sensor showed reasonably high re-usability and reproducibility, with reliable results for laboratory and real-world samples.

SHIELDeNN: Online Accelerated Framework for Fault-Tolerant Deep Neural Network Architectures

Abstract: We propose SHIELDeNN, an end-to-end inference accelerator frame-work that synergizes the mitigation approach and computational resources to realize a low-overhead error-resilient Neural Network (NN) overlay. We develop a rigorous fault assessment paradigm to delineate a ground-truth fault-skeleton map for revealing the most vulnerable parameters in NN. The error-susceptible parameters and resource constraints are given to a function to find superior design. The error-resiliency magnitude offered by SHIELDeNN can be adjusted based on the given boundaries. SHIELDeNN methodology improves the error-resiliency magnitude of cnvW1A1 by 17.19% and 96.15% for 100 MBUs that target weight and activation layers, respectively.