Literature DB >> 30515042

Reactive Oxygen Species: the Dual Role in Physiological and Pathological Conditions of the Human Body.

Sanaa K Bardaweel1, Mustafa Gul2, Muhammad Alzweiri1, Aman Ishaqat1, Husam A ALSalamat1, Rasha M Bashatwah1.   

Abstract

Reactive oxygen species (ROS) are well-known for playing a dual role as destructive and constructive species. Indeed, ROS are engaged in many redox-governing activities of the cells for the preservation of cellular homeostasis. However, its overproduction has been reported to result in oxidative stress, which is considered as a deleterious process, and is involved in the damage of cell structures that causes various diseased states. This review provides a concise view on some of the current research published in this topic for an improved understanding of the key roles of ROS in diverse conditions of health and disease. Previous research demonstrated that ROS perform as potential signaling molecules to control several normal physiological functions at the cellular level. Additionally, there is a growing body of evidence supporting the role of ROS in various pathological states. The binary nature of ROS with their profitable and injurious characteristics indicates the complexities of their specific roles at a biological compartment and the difficulties in establishing convenient intervention procedures to treat ROS-related diseases.

Entities:  

Keywords:  Reactive oxygen species; cancer; free radicals; infertility; oxidative stress

Year:  2018        PMID: 30515042      PMCID: PMC6263229          DOI: 10.5152/eurasianjmed.2018.17397

Source DB:  PubMed          Journal:  Eurasian J Med        ISSN: 1308-8734


  142 in total

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  41 in total

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5.  Modulation of ASIC1a by reactive oxygen species through JFK signaling.

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Review 6.  Review on Bee Products as Potential Protective and Therapeutic Agents in Male Reproductive Impairment.

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9.  Assessment and Establishment of Correlation between Reactive Oxidation Species, Citric Acid, and Fructose Level in Infertile Male Individuals: A Machine-Learning Approach.

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