Effects of Low-Viscosity Sodium Hyaluronate Preparation on the Pulmonary Absorption of rh-Insulin in Rats

Purpose: A low-viscosity formulation for pulmonary delivery of rh-insulin as model peptide drugs was developed using a solution of sodium hyaluronate. Method: The effects of different concentrations and pH values of low-viscosity solutions of hyaluronate on the pulmonary absorption of rh-insulin were examined after intratracheal administration in rats. The permeation of fluorescein isothiocyanate (FITC)-dextran(molecular weight 4300; FD-4) and insulin through excised rat trachea in vitro were also examined. Results: The hyaluronate (2140 kDa) solutions (0.1% and 0.2%w/v) at pH 7.0 significantly enhanced the pharmacological availability (PAB) of insulin compared to the aqueous solution of insulin at pH 7.0. The absorptionenhancing effect at a concentration of 0.1% w/v hyaluronate was greater than that at a concentration of 0.2% w/v hyaluronate. Furthermore, the greatest absorptionenhancing effect was obtained, regardless of the molecular weight of hyaluronate, when the concentration of hyaluronate was adjusted to 0.47 µM. Absorption-enhancing effects were consistent with the effect of a 0.1% w/v hyaluronate preparation at pH 4.0 and 7.0 on the permeation of FITC-dextran and insulin through excised rat trachea in vitro. Conclusion: Low-viscosity hyaluronate preparation was shown to be a useful vehicle for pulmonary delivery of peptide drugs.     

Fuzzy controller for AUV robots based on machine learning and genetic algorithm

Artificial Life and Robotics - Marine robots play a crucial role in exploring and investigating underwater and seafloor environments, organisms, structures, and resources. In this study, we...     

Modeling and design of networked control systems using a stochastic switching systems approach

A networked control system (NCS) is a control system in which plants, sensors, controllers, and actuators are connected through communication networks. In this paper, we consider NCSs modeled by stochastic switching systems, and propose a new method for modeling and optimal control. First, a recursive representation of the expected value of the state is proposed. Next, after an over‐approximation of this recursive representation is derived, the optimal control problem is reduced to a linear programming problem. Finally, the effectiveness of the proposed method is shown by a numerical example. The proposed method provides us an easy‐to‐use control method for NCSs. © 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.