BackgroundCompared with the traditional oral administration form, injection administration is basically superior in terms of both biological availability and therapeutic effects. However, few researches have focused on the traditional Chinese medicinal injection due to the complicated constituents and the intricate mechanism of action.MethodsIn the present work, a novel systems pharmacology model, integrating ADME (absorption, distribution, metabolism, and excretion) filtering such as half-life evaluation, network targeting, pathway and systems analyses, is specifically developed for the identification of active compounds and the study of the mechanism of action of TCM injection, which is exemplified by Reduning injection confronting the influenza.ResultsThe ADME filter successfully identifies 35 bioactive compounds (31 molecules and 4 metabolites) from the Reduning injection. The systems analysis and experimental validation further reveal a new way of confronting influenza disease of this injection: 1) stimulating the immunomodulatory agents for immune response activation, and 2) regulating the inflammatory agents for anti-inflammation.ConclusionsThe novel systems pharmacology method used in this study has the potential to advance the understanding of the molecular mechanisms of action of multicomponent herbal injections, and provide clues to discovering more effective drugs against complex diseases.Electronic supplementary materialThe online version of this article (doi:10.1186/1472-6882-14-430) contains supplementary material, which is available to authorized users.
This paper presents a new robust design for the longitudinal autopilot of a tail-controlled, skid-to-turn missile based on equivalent-input-disturbance (EID) and generalized extended state observer (GESO) approach. Firstly, the nonlinear missile longitudinal dynamics is modeled as a linear formulation for angle-of-attack tracking with uncertainties and disturbances. Next, as a new method, EID-GESO-based control is proposed for disturbance rejection. The method regards the uncertainties and disturbances as a lumped disturbance, named as EID, and simultaneously attenuates it through estimation of linear GESO and simple feedback. Closed-loop stability of the method is also proved. The most important feature of the proposed method over the others is that there is no requirement for system transformation, differentiation of the measured output, full system state available, exact plant model or any information about uncertainties and disturbances. Subsequently, the method is applied to robust longitudinal autopilot design and the feasibility is illustrated by numerical simulations. Finally, a performance comparison with some notable designs under considerable uncertainties and disturbances is implemented to demonstrate the effectiveness and robustness of the proposed design.
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