Many reports confirm ulcers as an adverse effect of drugs such as nicorandil and aspirin. The exact responsible mechanisms of ulceration have until now not proved. Mucosal ulcers associated with the onset of ulcer are manifested by an increase in proinflammatory cytokine, excessive prostaglandin, and up-regulation of Endothilin-1 level, which directly impacts the release of leptin. These, released locally within mucosal tissues, have played a role in controlling the extent of local inflammatory responses and processes of mucosal repair.
This study was designed to find out the correlation of plasma leptin and prostaglandin levels as a possible mechanism of oral ulcer formation as an adverse effect of nicorandil. The effect of nicorandil for inducing ulceration was assessed. The plasma leptin and prostaglandin E2 for the tested groups in relation to the studied parameters (gender, and daily body weight change) were estimated in albino rats.
Nicorandil causes mucous membrane damage, inflammation, and ulceration. A significant reduction of plasma leptin level, which was dose-dependent, and a non-significant reduction of serum prostaglandin E2 level. The mechanisms of ulcer induction as an adverse effect of nicorandil can be related to dose-dependant leptin and prostaglandin E2 levels, which affects on repair and healing process.
Keywords: Nicorandil, Leptin, Prostaglandin E2, Ulcer.
FG Mohammed, HM Al-Dabbas, Iraqi journal of science, 2018 - Cited by 6
In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve
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