Background and purpose:
Dracocephalum kotschyi
(
Zaringiah
) is a fragrant wild medicinal plant found in Iran. Traditionally, it is used for the treatment of rheumatism, asthma, and gastrointestinal ailments. So far no investigation has been done on the beneficial or side effects of
D. kotschyi
on peptic ulcer. Therefore, this research was performed to find out whether
D. kotschyi
extract would induce peptic ulcer or could alleviate existing peptic ulcer.
Experimental approach:
Effect of hydroalcoholic (DKHE) and flavonoid extracts (DKFE) of
D. kotschyi
were determined in normal or indomethacin-induced gastric ulcer rats (n = 6) and compared with the vehicle and ranitidine treated controls. All the treatments were carried out orally and 24 h later the stomach mucus was visually examined for peptic ulcers. A section of the stomach was taken for microscopic histopathological examinations while another section of the stomach was used for measurement of myeloperoxidase (MPO) and malondialdehyde (MDA) activities.
Findings/Results:
Oral administration of the DKHE and DKFE alone, did not cause any sign of gastric ulcer induction. The
D. kotschyi
extracts not only didn’t aggravate the induced ulcer but also significantly prevented the severity of gastric ulcer induction by indomethacin. In addition, DKHE and DKFE inhibited MPO (up to 58.2%) and MDA (up to 44.2%) activities indicating their anti-inflammatory and antioxidant potential action on the stomach-induced ulcer.
Conclusion and implication:
Usage of
D. kotschyi
extracts is not associated with gastric ulcer induction and its co-administration with NSAIDs would be beneficial for controlling both the inflammation and preventing gastric ulcer in diseases such as rheumatism.
This paper presents parameter estimation of Permanent Magnet Synchronous Motor (PMSM) using a combinatorial algorithm. Nonlinear fourth-order space state model of PMSM is selected. This model is rewritten to the linear regression form without linearization. Noise is imposed to the system in order to provide a real condition, and then combinatorial Orthogonal Projection Algorithm and Recursive Least Squares (OPA&RLS) method is applied in the linear regression form to the system. Results of this method are compared to the Orthogonal Projection Algorithm (OPA) and Recursive Least Squares (RLS) methods to validate the feasibility of the proposed method. Simulation results validate the efficacy of the proposed algorithm.
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