Background Methotrexate (MTX) is a classical folic acid antagonist widely used in the treatment of malignant and non-malignant disorders. However, its clinical application is often restricted by concomitant adverse effects, including renal damage. Numerous studies have highlighted the role of oxidative stress and inflammation in mediating MTX-related nephrotoxicity. Therefore, the current study aimed to explore the possible renoprotective action of Citronellol (CT), a natural compound with prominent antioxidant and anti-inflammatory activities, against nephrotoxicity induced by MTX. Methods To fulfill our objective, 24 adult male Wistar rats were randomly allocated into four groups: control, MTX, 100 mg/kg CT plus MTX and 200 mg/kg CT plus MTX. At the end of the study, the experimental rats were anesthetized, blood samples were collected for biochemical assays, and the kidneys were surgically removed for biochemical and gene expression analyses, after which all rats were sacrificed by exsanguination. Results Compared to the MTX-treated group, our results revealed that pre-supplementation with 100 or 200 mg/kg CT remarkably ameliorated renal damage biomarkers, including serum urea, serum creatinine, and kidney injury molecule-1 (KIM-1). In addition, pre-treatment with 100 or 200 mg/kg CT enhanced the activity of the antioxidant enzymes superoxide dismutase (SOD) and glutathione peroxidase (GPx), diminished renal malondialdehyde (MDA) contents, and attenuated inflammation by suppressing renal nuclear factor kappa B (NF-κB) signaling and diminishing tumor necrosis factor-alpha (TNF-α) gene expression. Moreover, pre-treatment with 200 mg/kg CT markedly reduced interleukin-1 beta (IL-1β) gene expression. Conclusion Our findings demonstrate, for the first time, that CT can serve as a new promising agent for mitigating nephrotoxicity induced by MTX through its antioxidant and anti-inflammatory properties.
This study investigated the effect of applying an external magnetic field on the characteristics of laser-induced plasma, such as its parameters plasma, magnetization properties, emission line intensities, and plasma coefficients, for plasma induced from zinc oxide: aluminum composite (ZO:AL) at an atomic ratio of 0.3 %. Plasma properties include magnetization and emission line intensities. The excitation was done by a pulsed laser of Nd:YAG with 400 mJ energy at atmospheric pressure. Both the electron temperature and number density were determined with the help of the Stark effect principle and the Boltzmann-Plot method. There was a rise in the amount of (ne) and (Te) that was produced
... Show MoreThe liver is the primary organ for drug metabolism, elimination, Cyclophosphamid is the classical alkylating agent nitrogen mustard, its metabolism into two cytotoxic metabolites, and increase reactive oxygen species that is make liver toxicity. Safranal as the most abundant chemical in saffron essential oil, it have anti-oxidant, anti-inflammatory, antiapoptic and free radical scavenger activity. The aim of study is to assess the protective effects of safranal on the cyclophosphamide-induce liver toxicity in rat model. This occur by using five different groups of rats; control group, treatment group, cyclophosamide group (intraperitoneal i.p), cyclophosamide and (50mg and 100mg) oral safranal treatment groups. This study showed this pro
... Show MoreDielectric barrier discharges (DBD) can be described as the presence of contact with the discharge of one or more insulating layers located between two cylindrical or flat electrodes connected to an AC/pulse dc power supply. In this work, the properties of the plasma generated by dielectric barrier discharge (DBD) system without and with a glass insulator were studied. The plasma was generated at a constant voltage of 4 kV and fixed distance between the electrodes of 5 mm, and with a variable flow rate of argon gas (0.5, 1, 1.5, 2 and 2.5) L/min. The emission spectra of the DBD plasmas at different flow rates of argon gas have been recorded. Boltzmann plot method was used to calculate the plasma electron temperature (Te), and Stark broadeni
... Show MoreTo learn how the manner of preparation influences film development, this study examined film expansion under a variety of deposition settings. To learn about the membrane’s properties and to ascertain the optimal pretreatment conditions, which are represented by ambient temperature and pressure, Laser pressure of 2.5[Formula: see text]m bar, the laser energy density of 500[Formula: see text]mJ, distortion ratio ([Formula: see text]) as a function of laser pulse count, all achieved with the double-frequency Nd: YAG laser operating in quality-factor mode at 1064[Formula: see text]nm. MgxZn[Formula: see text] films of thickness [Formula: see text][Formula: see text]nm were deposited on glass substrates at pulse
... Show MoreIn this work, the elemental constituents of smoker and nonsmoker
teeth samples of human were analyzed by Laser induced breakdown
spectroscopy method (LIBS). Many elements have been detected in
the healthy teeth samples, the important once are Ca, P, Mg, Fe, Pb
and Na. Many differences were found between (female and male)
teeth in Ca, P, Mg, Na and Pb contents. The concentrations of most
toxic elements were found significantly in the smoker group. The
maximum concentrations of toxic elements such as Pb, Cd and Co
were found in older male age above 60 year. Also, it was found that
the minimum concentrations of trace elements such as Ca, P and Na
exist in this age group. From these results it is clear that the
In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor
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