A L463^5 Box-Behnken design was used for developing a model to predict and optimize the molecular weight （Mw ） of polypropylene （PP） ; a second-order polynomial regression equation was derived to predict responses...A L463^5 Box-Behnken design was used for developing a model to predict and optimize the molecular weight （Mw ） of polypropylene （PP） ; a second-order polynomial regression equation was derived to predict responses. The significance of variables and their interactions were tested by means of the ANOVA with 95% confidence limits; the standardized effects were investigated by Pareto chart, the optimum values of the selected variables were obtained by analyzing the response surface contour plots. The optimized Mw value of 1. 217 × 10^5 g/mol was very close to the industrial value （ （ 1.22 ±0. 004） ×10^6 g/tool） at the optimum values.展开更多
<strong>Background: </strong>Recent decades witnessed a significant growth in terms of phytocompounds based therapeutics, extensively explored for almost all types of existing disorders. They have also bee...<strong>Background: </strong>Recent decades witnessed a significant growth in terms of phytocompounds based therapeutics, extensively explored for almost all types of existing disorders. They have also been widely investigated in Neurodegenerative disorders (NDDs) and Chlorogenic acid (CGA), a polyphenolic compound having potential anti-inflammatory and anti-oxidative properties, emerged as a promising compound in ameliorating NDDs. Owing to its poor stability, bioavailability and release kinetics, CGA needed a suitable nanocarrier based pharmaceutical design for targeting NDDs. <strong>Objective: </strong>The current study is aimed at the <em>in-silico</em> validation of CGA as an effective therapeutic agent targeting various NDDs followed by the fabrication of polymeric nanoparticles-based carrier system to overcome its pharmacological limitations and improve its stability. <strong>Methods:</strong> A successful <em>in-silico</em> validation using molecular docking techniques along with synthesis of CGA loaded polymeric nanoparticles (CGA-NPs) by ionic gelation method was performed. The statistical optimisation of the developed CGA-NPs was done by Box Behnken method and then the optimized formulation of CGA-NPs was characterised using particle size analysis (PSA), Transmission electron microscopy (TEM), Fourier Transform Infrared spectroscopy (FTIR) along with in-vitro release kinetics analysis.<strong> Results & Conclusion:</strong> The results attained exhibited average particle size of 101.9 ± 1.5 nm, Polydispersibility (PDI) score of 0.065 and a ZP of <span style="white-space:nowrap;">−</span>17.4 mV. On a similar note, TEM results showed a size range of CGA-NPs between 90 - 110 nm with a spherical shape of NPs. Also, the data from in-vitro release kinetics showed a sustained release of CGA from the NPs following the first-order kinetics suggesting the appropriate designing of nanoformulation.展开更多
基金Supported by the R&D Program of Catalyst Company,SINOPEC(G8101-11-ZS-0016*)
文摘A L463^5 Box-Behnken design was used for developing a model to predict and optimize the molecular weight （Mw ） of polypropylene （PP） ; a second-order polynomial regression equation was derived to predict responses. The significance of variables and their interactions were tested by means of the ANOVA with 95% confidence limits; the standardized effects were investigated by Pareto chart, the optimum values of the selected variables were obtained by analyzing the response surface contour plots. The optimized Mw value of 1. 217 × 10^5 g/mol was very close to the industrial value （ （ 1.22 ±0. 004） ×10^6 g/tool） at the optimum values.
文摘<strong>Background: </strong>Recent decades witnessed a significant growth in terms of phytocompounds based therapeutics, extensively explored for almost all types of existing disorders. They have also been widely investigated in Neurodegenerative disorders (NDDs) and Chlorogenic acid (CGA), a polyphenolic compound having potential anti-inflammatory and anti-oxidative properties, emerged as a promising compound in ameliorating NDDs. Owing to its poor stability, bioavailability and release kinetics, CGA needed a suitable nanocarrier based pharmaceutical design for targeting NDDs. <strong>Objective: </strong>The current study is aimed at the <em>in-silico</em> validation of CGA as an effective therapeutic agent targeting various NDDs followed by the fabrication of polymeric nanoparticles-based carrier system to overcome its pharmacological limitations and improve its stability. <strong>Methods:</strong> A successful <em>in-silico</em> validation using molecular docking techniques along with synthesis of CGA loaded polymeric nanoparticles (CGA-NPs) by ionic gelation method was performed. The statistical optimisation of the developed CGA-NPs was done by Box Behnken method and then the optimized formulation of CGA-NPs was characterised using particle size analysis (PSA), Transmission electron microscopy (TEM), Fourier Transform Infrared spectroscopy (FTIR) along with in-vitro release kinetics analysis.<strong> Results & Conclusion:</strong> The results attained exhibited average particle size of 101.9 ± 1.5 nm, Polydispersibility (PDI) score of 0.065 and a ZP of <span style="white-space:nowrap;">−</span>17.4 mV. On a similar note, TEM results showed a size range of CGA-NPs between 90 - 110 nm with a spherical shape of NPs. Also, the data from in-vitro release kinetics showed a sustained release of CGA from the NPs following the first-order kinetics suggesting the appropriate designing of nanoformulation.
