Proliposomes were used to improve the solubility and oral bioavailability of nifedipine. Nifedipine proliposomes were prepared by methanol injection-spray drying method. The response surface method was used to optimize formulation to enhance the encapsulation efficiency (EE%) of nifedipine. The particle size of nifedipine proliposomes after rehydration was 114 nm. Surface morphology of nifedipine proliposomes was observed by a scanning electron microscope (SEM) and interaction of formulation ingredients was assessed by differential scanning calorimetry (DSC). The solubility of nifedipine is improved 24.8 times after forming proliposomes. In vitro release experiment, nifedipine proliposomes had a control release effect, especially in simulated gastric fluid. In vivo, nifedipine proliposomes significantly improved the bioavailability of nifedipine. The area under the concentration-time curve (AUC0–∞) of nifedipine proliposomes was about 10 times than nifedipine after oral administration. The elimination half-life (T1/2β) of nifedipine was increased from 1.6 h to 6.6 h. In conclusion, proliposomes was a promising system to deliver nifedipine through oral route and warranted further investigation.
People demand better acoustic comfort for higher travelling quality and security in aircraft. It is necessary to evaluate and predict the subjective annoyance caused by the noise in aircraft cabins. This study investigates the noise-induced annoyance in a large passenger aircraft. We
recorded the noise at 21 positions in the aircraft cabin without passengers and selected 21 stimuli during the cruising. Each stimulus has a duration of 5 seconds and a sound pressure level in the range of 72-81dB(A). The psychoacoustic parameters such as loudness, sharpness, roughness and
articulation index were also calculated. Twenty-four subjects evaluated the subjective annoyance of the stimuli by the absolute magnitude estimation method. Results showed the noise annoyance at the middle section of the cabin is significantly higher than that at the front or rear section.
The principal component analysis and correlation analysis found that annoyance is mainly affected by loudness, sharpness and roughness and dominated by loudness. We proposed a multiple linear regression model between the subjective magnitudes of annoyance and the psychoacoustic parameters
to evaluate and predict the noise annoyance in the aircraft cabin well.
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