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Event: 1969

Key Event Title

The KE title should describe a discrete biological change that can be measured. It should generally define the biological object or process being measured and whether it is increased, decreased, or otherwise definably altered relative to a control state. For example “enzyme activity, decreased”, “hormone concentration, increased”, or “growth rate, decreased”, where the specific enzyme or hormone being measured is defined. More help

Increase, Oxidative Stress

Short name
The KE short name should be a reasonable abbreviation of the KE title and is used in labelling this object throughout the AOP-Wiki. The short name should be less than 80 characters in length. More help
Increase, Oxidative Stress

Biological Context

Structured terms, selected from a drop-down menu, are used to identify the level of biological organization for each KE. Note, KEs should be defined within a particular level of biological organization. Only KERs should be used to transition from one level of organization to another. Selection of the level of biological organization defines which structured terms will be available to select when defining the Event Components (below). More help
Level of Biological Organization

Cell term

Further information on Event Components and Biological Context may be viewed on the attached pdf.The biological context describes the location/biological environment in which the event takes place.  For molecular/cellular events this would include the cellular context (if known), organ context, and species/life stage/sex for which the event is relevant. For tissue/organ events cellular context is not applicable.  For individual/population events, the organ context is not applicable. More help

Organ term

Further information on Event Components and Biological Context may be viewed on the attached pdf.The biological context describes the location/biological environment in which the event takes place.  For molecular/cellular events this would include the cellular context (if known), organ context, and species/life stage/sex for which the event is relevant. For tissue/organ events cellular context is not applicable.  For individual/population events, the organ context is not applicable. More help

Key Event Components

Further information on Event Components and Biological Context may be viewed on the attached pdf.Because one of the aims of the AOP-KB is to facilitate de facto construction of AOP networks through the use of shared KE and KER elements, authors are also asked to define their KEs using a set of structured ontology terms (Event Components). In the absence of structured terms, the same KE can readily be defined using a number of synonymous titles (read by a computer as character strings). In order to make these synonymous KEs more machine-readable, KEs should also be defined by one or more “event components” consisting of a biological process, object, and action with each term originating from one of 22 biological ontologies (Ives, et al., 2017; See List). Biological process describes dynamics of the underlying biological system (e.g., receptor signalling). The biological object is the subject of the perturbation (e.g., a specific biological receptor that is activated or inhibited). Action represents the direction of perturbation of this system (generally increased or decreased; e.g., ‘decreased’ in the case of a receptor that is inhibited to indicate a decrease in the signalling by that receptor).Note that when editing Event Components, clicking an existing Event Component from the Suggestions menu will autopopulate these fields, along with their source ID and description. To clear any fields before submitting the event component, use the 'Clear process,' 'Clear object,' or 'Clear action' buttons. If a desired term does not exist, a new term request may be made via Term Requests. Event components may not be edited; to edit an event component, remove the existing event component and create a new one using the terms that you wish to add. More help

Key Event Overview

AOPs Including This Key Event

All of the AOPs that are linked to this KE will automatically be listed in this subsection. This table can be particularly useful for derivation of AOP networks including the KE. Clicking on the name of the AOP will bring you to the individual page for that AOP. More help
AOP Name Role of event in AOP Point of Contact Author Status OECD Status
Inhibition of Mt-ETC complexes leading to kidney toxicity KeyEvent Agnes Aggy (send email) Under development: Not open for comment. Do not cite


This is a structured field used to identify specific agents (generally chemicals) that can trigger the KE. Stressors identified in this field will be linked to the KE in a machine-readable manner, such that, for example, a stressor search would identify this as an event the stressor can trigger. NOTE: intermediate or downstream KEs in one AOP may function as MIEs in other AOPs, meaning that stressor information may be added to the KE description, even if it is a downstream KE in the pathway currently under development.Information concerning the stressors that may trigger an MIE can be defined using a combination of structured and unstructured (free-text) fields. For example, structured fields may be used to indicate specific chemicals for which there is evidence of an interaction relevant to this MIE. By linking the KE description to a structured chemical name, it will be increasingly possible to link the MIE to other sources of chemical data and information, enhancing searchability and inter-operability among different data-sources and knowledgebases. The free-text section “Evidence for perturbation of this MIE by stressor” can be used both to identify the supporting evidence for specific stressors triggering the MIE as well as to define broad chemical categories or other properties that classify the stressors able to trigger the MIE for which specific structured terms may not exist. More help

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) can be selected from an ontology. In many cases, individual species identified in these structured fields will be those for which the strongest evidence used in constructing the AOP was available in relation to this KE. More help

Life Stages

The structured ontology terms for life-stage are more comprehensive than those for taxa, but may still require further description/development and explanation in the free text section. More help

Sex Applicability

The authors must select from one of the following: Male, female, mixed, asexual, third gender, hermaphrodite, or unspecific. More help

Key Event Description

A description of the biological state being observed or measured, the biological compartment in which it is measured, and its general role in the biology should be provided. For example, the biological state being measured could be the activity of an enzyme, the expression of a gene or abundance of an mRNA transcript, the concentration of a hormone or protein, neuronal activity, heart rate, etc. The biological compartment may be a particular cell type, tissue, organ, fluid (e.g., plasma, cerebrospinal fluid), etc. The role in the biology could describe the reaction that an enzyme catalyses and the role of that reaction within a given metabolic pathway; the protein that a gene or mRNA transcript codes for and the function of that protein; the function of a hormone in a given target tissue, physiological function of an organ, etc. Careful attention should be taken to avoid reference to other KEs, KERs or AOPs. Only describe this KE as a single isolated measurable event/state. This will ensure that the KE is modular and can be used by other AOPs, thereby facilitating construction of AOP networks. More help

“Oxidative stress is traditionally defined as an imbalance between production of ROS and endogenous antioxidants” (Small et al., 2018). Reactive Oxygen Species (ROS), the core perpetrators of oxidative stress, are highly reactive free radical oxygen molecules (Turrens, 2003; Valko et al., 2005; Hancock et al., 2001). These free radicals are strong oxidants that in high amounts, could irreversibly damage the cell and its organelles. ROS, however, are not by default detrimental to cellular function but contribute to normal activities, under physiological conditions. Reactive oxygen species can behave as signaling molecules by oxidizing proteins, lipids, and polynucleotides (Zhao et al., 2019; Hancock et al., 2001; Gorlach et al., 2015). When present in tolerable amounts, superoxides (O2-) behave as signalling molecules important in cell proliferation, hypoxia adaption, and cell fate determination but when present in excess or unregulated, induce cell damage and death (Zhao et al., 2019). Under normal oxidative phosphorylation, approximately 1-2% of the oxygen reduced by mitochondria converts into reactive oxygen species (ROS) at intermediate steps of the respiratory chain, during electron transfer (Kowaltowski and Vercesi, 1998; Volka et al., 2005; Li et al., 2003). On top of ROS generation occurring during natural cell metabolism, several other mitochondrial enzymes, such as cytochrome P450, are linked to ROS production and, interestingly many of these systems are modulated by calcium (Gorlach et al., 2015; Hancock et al., 2001). The main reasons that these antioxidant systems are in place are to regulate the constant, regular production of ROS and their signalling functionality. Oxidative stress is defined as a disruption of the pro-oxidant-antioxidant balance, favouring pro-oxidants, potentially damaging cellular components (Sies, 1991). It is important to note the fact that oxidative stress is generally caused by one of three reasons: either there is a significant increase in ROS; or there is a significant decrease in antioxidant function; or the two factors working in tandem. This distinction is crucial in determining methods of assessment of oxidative stress.

Other than mitochondrial ROS production, one of the primary producers of superoxide (O2-) is NADPH, doing so by a single electron reduction of molecular oxygen (Panday et al., 2014). NADPH oxidase, is a cytosolic-membrane protein, implicated in host defence, cellular signalling, and gene expression regulation. It is thought to produce ROS partly for defence against microbial pathogens (Panday et al., 2014). Due to its volatile nature, once formed, O2 released into the inter-membrane space (IMS) by CIII inevitably generates hydrogen peroxide (H2O2), a reaction is catalyzed by superoxide dismutase (SOD) (Hancock et al., 2001). Once present, the fate of H2O2 is variable and its reduction to H2O can be catalyzed by glutathione peroxidase (GPx) or peroxisomal catalase. Otherwise, it can be further converted into highly reactive hydroxyl radicals, particularly in the presence of metal ions (Hancock et al., 2001; Valko et al., 2005; Adam-Vizi et al., 2010).

Under normal mitochondrial conditions, antioxidant enzymes and molecules – such as, superoxide dismutase, glutathione peroxidase, catalase, and glutathione – balance ROS generation by scavenging or binding to ROS (Santos et al., 2007). ROS disposal involves superoxide dismutase (SOD) converting O2- to H2O2, then detoxified into H2O by glutathione and catalase (Xu & Møller, 2010). Also, in case of mitochondrial damage or dysfunction, the antioxidant defence system may be impaired and its capacity drops. The resultant imbalance of the production and removal of ROS is oxidative stress. Due to the nature of oxidative stress induction and the short half-life of ROS, measuring oxidative stress through antioxidant function is a more accurate and effective way to determine the state of the cell. Oxidative stress behaves as a positive feedback loop, leading to the over-production of free-radicals as ROS further damage the mitochondria and antioxidant capacity continues to decrease (Hancock et al., 2001; Turrens, 2003; Valko et al., 2005). Antioxidant defenses can also be inhibited, further contributing to mitochondrial dysfunction; this is commonly induced by exposure to heavy metals (Blajszczak and Bonini, 2017). Due to the formation of this positive feedback loop, we experience a gap in knowledge as to which event initiated the cycle; was the increased ROS production the cause of mitochondrial dysfunction or did the mitochondrial dysfunction lead to increased ROS production?

Heavy metal exposure in aerobic organisms increases ROS formation through redox cycling, where metals with different valence states (for example Fe, Cu, and Cr) directly produce ROS as they are reduced by cellular antioxidants and then react with oxygen (Shaki et al., 2012; Shaki et al., 2013; Pourahmad et al., 2006; Santos et al., 2007). The production of highly reactive hydroxyl radicals under mitochondrial oxidative stress in the presence of transition metals occurs via the Fenton reaction or Haber-Weiss reaction (Hancock et al., 2001; Valko et al., 2005; Adam-Vizi et al., 2010). Metals have been shown to inhibit ROS-detoxifying enzymes. By binding to these enzymes, metals can inhibit their antioxidant functions, and cause an accumulation of ROS and increased synthesis of more antioxidants in order to combat the oxidative stress (Blajszczak and Bonini, 2017).

How It Is Measured or Detected

One of the primary considerations in evaluating AOPs is the relevance and reliability of the methods with which the KEs can be measured. The aim of this section of the KE description is not to provide detailed protocols, but rather to capture, in a sentence or two, per method, the type(s) of measurements that can be employed to evaluate the KE and the relative level of scientific confidence in those measurements. Methods that can be used to detect or measure the biological state represented in the KE should be briefly described and/or cited. These can range from citation of specific validated test guidelines, citation of specific methods published in the peer reviewed literature, or outlines of a general protocol or approach (e.g., a protein may be measured by ELISA).Key considerations regarding scientific confidence in the measurement approach include whether the assay is fit for purpose, whether it provides a direct or indirect measure of the biological state in question, whether it is repeatable and reproducible, and the extent to which it is accepted in the scientific and/or regulatory community. Information can be obtained from the OECD Test Guidelines website and the EURL ECVAM Database Service on Alternative Methods to Animal Experimentation (DB-ALM). ?


Assay Type & Measured Content Description Dose Range Studied

Assay Characteristics (Length / Ease of use/Accuracy)

ROS Formation in the Mitochondria assay


(Shaki et al., 2012)

“The mitochondrial ROS measurement was performed flow cytometry using DCFH-DA. Briefly, isolated kidney mitochondria were incubated with UA (0, 50, 100 and 200 μM) in respiration buffer containing (0.32 mM sucrose, 10 mM Tris, 20 mM Mops, 50 μM EGTA, 0.5 mM MgCl2, 0.1 mM KH2PO4 and 5 mM sodium succinate) [32]. In the interval times of 5, 30 and 60 min following the UA addition, a sample was taken and DCFH-DA was added (final concentration, 10 μM) to mitochondria and was then incubated for 10 min. Uranyl acetate-induced ROS generation in isolated kidney mitochondria were determined through the flow cytometry (Partec, Deutschland) equipped with a 488-nm argon ion laser and supplied with the Flomax software and the signals were obtained using a 530-nm bandpass filter (FL-1 channel). Each determination is based on the mean fluorescence intensity of 15,000 counts.” (Shaki et al., 2012) 0, 50, 100 and 200 μM of Uranyl Acetate

Long/ Easy

High accuracy

Mitochondrial Antioxidant Content Assay

Measuring GSH content

(Shaki et al., 2012)
“GSH content was determined using DTNB as the indicator and spectrophotometer method for the isolated mitochondria. The mitochondrial fractions (0.5 mg protein/ml) were incubated with various concentrations of uranyl acetate for 1 h at 30 °C and then 0.1 ml of mitochondrial fractions was added into 0.1 mol/l of phosphate buffers and 0.04% DTNB in a total volume of 3.0 ml (pH 7.4). The developed yellow color was read at 412 nm on a spectrophotometer (UV-1601 PC, Shimadzu, Japan). GSH content was expressed as μg/mg protein.” (Shaki et al., 2012)

0, 50, 100, or 200 μM Uranyl Acetate


H2O2 Production Assay

Measuring H2O2 Production in isolated mitochondria

(Heyno et al., 2008)
“Effect of CdCl2 and antimycin A (AA) on H2O2 production in isolated mitochondria from potato. H2O2 production was measured as scopoletin oxidation. Mitochondria were incubated for 30 min in the measuring buffer (see the Materials and Methods) containing 0.5 mM succinate as an electron donor and 0.2 µM mesoxalonitrile 3‐chlorophenylhydrazone (CCCP) as an uncoupler, 10 U horseradish peroxidase and 5 µM scopoletin.” (Heyno et al., 2008)

0, 10, 30  μM Cd2+

2  μM antimycin A

Flow Cytometry ROS & Cell Viability

(Kruiderig et al., 1997)
For determination of ROS, samples taken at the indicated time points were directly transferred to FACScan tubes. Dih123 (10 mM, final concentration) was added and cells were incubated at 37°C in a humidified atmosphere (95% air/5% CO2) for 10 min. At t 5 9, propidium iodide (10 mM, final concentration) was added, and cells were analyzed by flow cytometry at 60 ml/min. Nonfluorescent Dih123 is cleaved by ROS to fluorescent R123 and detected by the FL1 detector as described above for Dc (Van de Water 1995)”  




Detection of hydrogen peroxide production

(Yuan et al., 2016)

Intracellular ROS production was measured using DCFH-DA as a probe. Hydrogen peroxide oxidizes DCFH to DCF. The probe is hydrolyzed intracellularly to DCFH carboxylate anion. No direct reaction with H2O2 to form fluorescent production.   

0-400 µM

Long/ Easy

High accuracy

H2-DCF-DA Assay

Detection of superoxide production

(Thiebault et al., 2007)

This dye is a stable nonpolar compound which diffuses readily into the cells and yields H2-DCF. Intracellular OH or ONOO- react with H2-DCF when cells contain peroxides, to form the highly fluorescent compound DCF, which effluxes the cell. Fluorescence intensity of DCF is measured using a fluorescence spectrophotometer. 0–600 µM

Long/ Easy

High accuracy

CM-H2DCFDA Assay **Come back and explain the flow cytometry determination of oxidative stress from Pan et al. (2009)**    

Domain of Applicability

This free text section should be used to elaborate on the scientific basis for the indicated domains of applicability and the WoE calls (if provided). While structured terms may be selected to define the taxonomic, life stage and sex applicability (see structured applicability terms, above) of the KE, the structured terms may not adequately reflect or capture the overall biological applicability domain (particularly with regard to taxa). Likewise, the structured terms do not provide an explanation or rationale for the selection. The free-text section on evidence for taxonomic, life stage, and sex applicability can be used to elaborate on why the specific structured terms were selected, and provide supporting references and background information.  More help

Oxidative stress can happen in all forms of life.

Evidence for Perturbation by Stressor


Kruidering et al. (1997) examined the effect of platinum on pig kidneys and found that it was able to induce significant dose-dependant ROS formation within 20 minutes of treatment administration.


In a study of the effects of aluminum treatment on rat kidneys, Al Dera (2016) found that renal GSH, SOD, and GPx levels were significantly lower in the treated groups, while lipid peroxidation levels were significantly increased.


Belyaeva et al. (2012) investigated the effect of cadmium treatment on human kidney cells. They found that cadmium was the most toxic when the sample was treated with 500 μM for 3 hours (Belyaeva et al., 2012). As this study also looked at mercury, it is worth noting that mercury was more toxic than cadmium in both 30-minute and 3-hour exposures at low concentrations (10-100 μM) (Belyaeva et al., 2012).

Wang et al. (2009) conducted a study evaluating the effects of cadmium treatment on rats and found that the treated group showed a significant increase in lipid peroxidation. They also assessed the effects of lead in this study, and found that cadmium can achieve a very similar level of lipid peroxidation at a much lower concentration than lead can, implying that cadmium is a much more toxic metal to the kidney mitochondria than lead is (Wang et al., 2009). They also found that when lead and cadmium were applied together they had an additive effect in increasing lipid peroxidation content in the renal cortex of rats (Wang et al., 2009).

Jozefczak et al. (2015) treated Arabidopsis thaliana wildtype, cad2-1 mutant, and vtc1-1 mutant plants with cadmium to determine the effects of heavy metal exposure to plant mitochondria in the roots and leaves. They found that total GSH/GSG ratios were significantly increased after cadmium exposure in the leaves of all sample varieties and that GSH content was most significantly decreased for the wildtype plant roots (Jozefczak et al., 2015).

Andjelkovic et al. (2019) also found that renal lipid peroxidation was significantly increased in rats treated with 30 mg/kg of cadmium.


Belyaeva et al. (2012) conducted a study which looked at the effects of mercury on human kidney cells, they found that mercury was the most toxic when the sample was treated with 100 μM for 30 minutes.

Buelna-Chontal et al. (2017) investigated the effects of mercury on rat kidneys and found that treated rats had higher lipid peroxidation content and reduced cytochrome c content in their kidneys.


In Shaki et al.’s article (2012), they found rat kidney mitochondria treated with uranyl acetate caused increased formation of ROS, increased lipid peroxidation, and decreased GSH content when exposed to 100 μM or more for an hour.

Hao et al. (2014), found that human kidney proximal tubular cells (HK-2 cells) treated with uranyl nitrate for 24 hours with 500 μM showed a 3.5 times increase in ROS production compared to the control. They also found that GSH content was decreased by 50% of the control when the cells were treated with uranyl nitrate (Hao et al., 2014).


Bhadauria and Flora (2007) studied the effects of arsenic treatment on rat kidneys. They found that lipid peroxidation levels were increased by 1.5 times and the GSH/GSSG ratio was decreased significantly (Bhadauria and Flora, 2007).

Kharroubi et al. (2014) also investigated the effect of arsenic treatment on rat kidneys and found that lipid peroxidation was significantly increased, while GSH content was significantly decreased.

In their study of the effects of arsenic treatment on rat kidneys, Turk et al. (2019) found that lipid peroxidation was significantly increased while GSH and GPx renal content were decreased.


Miyayama et al. (2013) investigated the effects of silver treatment on human bronchial epithelial cells and found that intracellular ROS generation was increased significantly in a dose-dependant manner when treated with 0.01 to 1.0 μM of silver nitrate.


Chtourou et al. (2012) investigated the effects of manganese treatment on rat kidneys. They found that manganese treatment caused significant increases in ROS production, lipid peroxidation, urinary H2O2 levels, and PCO production. They also found that intracellular GSH content was depleted in the treated group (Chtourou et al., 2012).


Tyagi et al. (2011) conducted a study of the effects of nickel treatment on rat kidneys. They found that the treated rats showed a significant increase in kidney lipid peroxidation and a significant decrease in GSH content in the kidney tissue (Tyagi et al., 2011).


Yeh et al. (2011) investigated the effects of zinc treatment on rat kidneys and found that treatment with 150 μM or more for 2 weeks or more caused a time- and dose-dependant increase in lipid peroxidation. They also found that renal GSH content was decreased in the rats treated with 150 μM or more for 8 weeks (Yeh et al., 2011).

It should be noted that Hao et al. (2014) found that rat kidneys exposed to lower concentrations of zinc (such as 100 μM) for short time periods (such as 1 day), showed a protective effect against toxicity induced by other heavy metals, including uranium. Soussi, Gargouri, and El Feki (2018) also found that pre-treatment with a low concentration of zinc (10 mg/kg treatment for 15 days) protected the renal cells of rats were from changes in varying oxidative stress markers, such as lipid peroxidation, protein carbonyl, and GPx levels.


Huerta-García et al. (2014) conducted a study of the effects of titanium nanoparticles on human and rat brain cells. They found that both the human and rat cells showed time-dependant increases in ROS when treated with titanium nanoparticles for 2 to 6 hours (Huerta-García et al., 2014). They also found elevated lipid peroxidation that was induced by the titanium nanoparticle treatment of human and rat cell lines in a time-dependant manner (Huerta-García et al., 2014).

Liu et al. (2010) also investigated the effects of titanium nanoparticles, however they conducted their trials on rat kidney cells. They found that ROS production was significantly increased in a dose dependant manner when treated with 10 to 100 μg/mL of titanium nanoparticles (Liu et al., 2010).

Pan et al. (2009) treated human cervix carcinoma cells with gold nanoparticles (Au1.4MS) and found that intracellular ROS content in the treated cells increased in a time-dependant manner when treated with 100 μM for 6 to 48 hours. They also compared the treatment with Au1.4MS gold nanoparticles to treatment with Au15MS treatment, which are another size of gold nanoparticle (Pan et al., 2009). The Au15MS nanoparticles were much less toxic than the Au1.4MS gold nanoparticles, even when the Au15MS nanoparticles were applied at a concentration of 1000 μM (Pan et al., 2009). When investigating further markers of oxidative stress, Pan et al. (2009) found that GSH content was greatly decreased in cells treated with gold nanoparticles.

Ferreira et al. (2015) also studied the effects of gold nanoparticles. They exposed rat kidneys to GNPs-10 (10 nm particles) and GNPs-30 (30 nm particles), and found that lipid peroxidation and protein carbonyl content in the rat kidneys treated with GNPs-30 and GNPs-10, respectively, were significantly elevated.


List of the literature that was cited for this KE description. Ideally, the list of references, should conform, to the extent possible, with the OECD Style Guide ( (OECD, 2015). More help

Adam-Vizi, V., & Starkov, A. A. (2010). Calcium and mitochondrial reactive oxygen species generation: How to read the facts. Journal of Alzheimer's Disease : JAD, 20 Suppl 2, S413-S426. doi:10.3233/JAD-2010-100465

Al Dera, H. S. (2016). Protective effect of resveratrol against aluminum chloride induced nephrotoxicity in rats. Saudi Med J, 37(4), 369-378. doi:10.15537/smj.2016.4.13611

Andjelkovic, M., Djordjevic, A. B., Antonijevic, E., Antonijevic, B., Stanic, M., Kotur-Stevuljevic, J., . . . Bulat, Z. (2019). Toxic effect of acute cadmium and lead exposure in rat blood, liver, and kidney. International Journal of Environmental Research and Public Health, 16, 247. doi:10.3390/ijerph16020274

Barbier, O., Jcquillet, G., Tauc, M., Cougnon, M., & Poujeol, P. (2005). Effect of heavy metals on, and handling by, the  kidney. Nephron Physiology, 99, 105-110. doi:10.1159/000083981

Belyaeva, E. A., Sokolova, T. V., Emelyanova, L. V., & Zakharova, I. O. (2012). Mitochondrial electron transport chain in heavy metal-induced neurotoxicity : Effects of cadmium , mercury , and copper. Thescientificworld, 2012, 1-14. doi:10.1100/2012/136063

Bhadauria, S., & Flora, S. J. S. (2007). Response of arsenic-induced oxidative stress, DNA damage, and metal imbalance to combined administration of DMSA and monoisoamyl-DMSA during chronic arsenic poisoning in rats. Cell Biol Toxicol, 23, 91-104. doi:10.1007/s10565-006-0135-8

Blajszczak, C., & Bonini, M. G. (2017). Mitochondria targeting by environmental stressors : Implications for redox cellular signaling. Toxicology, 391, 84-89. doi:10.1016/j.tox.2017.07.013

Buelna-Chontal, M., Franco, M., Hernandez-Esquivel, L., Pavon, N., Rodriguez-Zalvala, J. S., Correa, F., . . . Chavez, E. (2017). CDP-choline circumvents mercury-induced mitochondrial damage and renal dysfunction. Cell Biology International, 41, 1356-1366. doi:10.1002/cbin.10871

Chtourou, Y., Garoui, E. m., Boudawara, T., & Zeghal, N. (2014). Protective role of silymarin against manganese-induced nephrotoxicity and oxidative stress in rat. Environ Toxicol, 29, 1147-1154. doi:10.1002/tox.21845

Ferreira, G. K., Cardoso, E., Vuolo, F. S., Michels, M., Zanoni, E. T., Carvalho-Silva, M., . . . Paula, M. M. S. (2015). Gold nanoparticles alter parameters of oxidative stress and energy metabolism in organs of adult rats. Biochem. Cell Biol., 93, 548-557. doi:10.1139/bcb-2015-0030

Görlach, A., Bertram, K., Hudecova, S., & Krizanova, O. (2015). Calcium and ROS: A mutual interplay. Redox Biology, 6, 260-271. doi:doi:10.1016/j.redox.2015.08.010

Hancock, J. T., Desikan, R., & Neill, S. J. (2001). Role of reactive oxygen species in cell signalling pathways. Biochemical Society Transactions, 29(Pt 2), 345-350. doi:10.1042/0300-5127:0290345 [doi]

Hao, Y., Huang, J., Liu, C., Li, H., Liu, J., Zeng, Y., . . . Li, R. (2016). Differential protein expression in metallothionein protection from depleted uranium-induced nephrotoxicity. Scientific Reports, doi:10.1038/srep38942

Heyno, E., Klose, C., & Krieger-Liszkay, A. (2008). Origin of cadmium-induced reactive oxygen species production: Mitochondrial electron transfer versus plasma membrane NADPH oxidase. New Phytologist, 179, 687-699. doi:10.1111/j.1469-8137.2008.02512.x

Huerta-García, E., Perez-Arizti, J. A., Marquez-Ramirez, S. G., Delgado-Buenrostro, N. L., Chirino, Y. I., Iglesias, G. G., & Lopez-Marure, R. (2014). Titanium dioxide nanoparticles induce strong oxidative stress and mitochondrial damage in glial cells. Free Radical Biology and Medicine, 73, 84-94. doi:10.1016/j.freeradbiomed.2014.04.026

Jozefczak, M., Bohler, S., Schat, H., Horemans, N., Guisez, Y., Remans, T., . . . Cuypers, A. (2015). Both the concentration and redox state of glutathione and ascorbate influence the sensitivity of arabidopsis to cadmium. Annals of Botany, 116(4), 601-612. doi:10.1093/aob/mcv075

Kehrer, J. P. (2000). The Haber–Weiss reaction and mechanisms of toxicity. Toxicology, 149(1), 43-50. doi:

Kharroubi, W., Dhibi, M., Mekni, M., Haouas, Z., Chreif, I., Neffati, F., . . . Sakly, R. (2014). Sodium arsenate induce changes in fatty acids profiles and oxidative damage in kidney of rats. Environ Sci Pollut Res, 21, 12040-12049. doi:10.1007/s11356-014-3142-y

Kowaltowski, A. J., & Vercesi, A. E. (1999). Mitochondrial damage induced by conditions of oxidative stress. Free Radical Biology and Medicine, 26(3), 463-471. doi:

Kruidering, M., Van De Water, B., De Heer, E., Mulder, G. J., & Nagelkerke, J. F. (1997). Cisplatin-induced nephrotoxicity in porcine proximal tubular cells: Mitochondrial dysfunction by inhibition of complexes I to IV of the respiratory chain. The Journal of Pharmacology and Experimental Therapeutics, 280(2), 638-649.

Li, N., Ragheb, K., Lawler, G., Sturgis, J., Melendez, J. A., & Robinson, J. P. (2003). Mitochondrial complex I inhibitor rotenone induced apoptosis through enhancing mitochondrial reactive oxygen species production. The Journal of Biological Chemistry, 278(10), 8516-8525.

Liang, Shih-Shin & Shiue, Yow-Ling & Kuo, Chao Jen & Guo, Su-Er & Liao, Wei-Ting & Tsai, Eing. (2013). Online Monitoring Oxidative Products and Metabolites of Nicotine by Free Radicals Generation with Fenton Reaction in Tandem Mass Spectrometry. TheScientificWorldJournal. 2013. 189162. 10.1155/2013/189162.

Liu, S., Xu, L., Zhang, T., Ren, G., & Yang, Z. (2010). Oxidative stress and apoptosis induced by nanosized titanium dioxide in PC12 cells. Toxicology, 267, 172-177. doi:10.1016/j.tox.2009.11.012

Lunyera, J., & Smith, S. R. (2017). Heavy metal nephropathy: Considerations for exposure analysis. Kidney International, 92, 548-550. doi:

Miyayama, T., Arai, Y., Suzuki, N., & Hirano, S. (2013). Mitochondrial electron transport is inhibited by disappearance of metallothionein in human bronchial epithelial cells follwoing exposure to silver nitrate. Toxicology, 305, 20-29. doi:10.1016/j.tox.2013.01.004

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