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Relationship: 1690

Title

A descriptive phrase which clearly defines the two KEs being considered and the sequential relationship between them (i.e., which is upstream, and which is downstream). More help

Oxidative Stress leads to Cell injury/death

Upstream event

The causing Key Event (KE) in a Key Event Relationship (KER). More help

Oxidative Stress

Downstream event

The responding Key Event (KE) in a Key Event Relationship (KER). More help

Cell injury/death

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes.Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

AOP Name	Adjacency	Weight of Evidence	Quantitative Understanding	Point of Contact	Author Status	OECD Status
Binding of electrophilic chemicals to SH(thiol)-group of proteins and /or to seleno-proteins involved in protection against oxidative stress during brain development leads to impairment of learning and memory	non-adjacent	High	High	Brendan Ferreri-Hanberry (send email)	Open for citation & comment	WPHA/WNT Endorsed

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) that help to define the biological applicability domain of the KER.In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER. More help

Term	Scientific Term	Evidence	Link
rat	Rattus norvegicus	High	NCBI
mouse	Mus musculus	High	NCBI
zebra fish	Danio rerio	High	NCBI
salmonid fish	salmonid fish	High	NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help

Sex	Evidence
Male
Female

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER. More help

Term	Evidence
All life stages	High

Key Event Relationship Description

Provides a concise overview of the information given below as well as addressing details that aren’t inherent in the description of the KEs themselves. More help

Oxidative stress (OS) as a concept in redox biology and medicine has been formulated in 1985 (Sies, 2015). OS is intimately linked to cellular energy balance and comes from the imbalance between the generation and detoxification of reactive oxygen and nitrogen species (ROS/RNS) or from a decay of the antioxidant protective ability. OS is characterized by the reduced capacity of endogenous systems to fight against the oxidative attack directed towards target biomolecules (Wang and Michaelis, 2010; Pisoschi and Pop, 2015). Glutathione, the most important redox buffer in cells (antioxidant), cycles between reduced glutathione (GSH) and oxidized glutathione disulfide (GSSG), and serves as a vital sink for control of ROS levels in cells (Reynolds et al., 2007). Several case-control studies have reported the link between lower concentrations of GSH, higher levels of GSSG and the development of diseases (Rossignol and Frye, 2014). OS can cause cellular damage and subsequent cell death because the ROS oxidize vital cellular components such as lipids, proteins, and nucleic acids (Gilgun-Sherki, Melamed and Offen, 2001; Wang and Michaelis, 2010).

The central nervous system is especially vulnerable to free radical damage since it has a high oxygen consumption rate, an abundant lipid content and reduced levels of antioxidant enzymes (Coyle and Puttfarcken, 1993; Markesbery, 1997). It has been show that the developing brain is particularly vulnerable to neurotoxicants and OS due to differentiation processes, changes in morphology, lack of physiological barriers and less intrinsic capacity to cope with cellular stress (Grandjean and Landrigan, 2014; Sandström et al., 2017). However, it has to be noted that neural stem cells distinguish themeselves from post-mitotic neural cells by their lower ROS levels and higher expression of the key antioxidant enzymes glutathione peroxidase. This increased "vigilance" of antioxidant mechanisms might represent an innate characteristic of NSCs, which not only defines their cell fate, but also helps them to encounter oxidative stress (Madhavan et al., 2006).

OS has been linked to brain aging, neurodegenerative diseases, and other related adverse conditions. There is evidence that free radicals play a role in cerebral ischemia-reperfusion, head injury, Parkinson’s disease, amyotrophic lateral sclerosis, Down’s syndrome, and Alzheimer’s disease due to cellular damage (Markesbery, 1997; Gilgun-Sherki, Melamed and Offen, 2001; Wang and Michaelis, 2010). OS has also been linked to neurodevelopmental diseases and deficits like autism spectrum disorder and postnatal motor coordination deficits (Wells et al., 2009; Rossignol and Frye, 2014; Bhandari and Kuhad, 2015).

Evidence Collection Strategy

Include a description of the approach for identification and assembly of the evidence base for the KER. For evidence identification, include, for example, a description of the sources and dates of information consulted including expert knowledge, databases searched and associated search terms/strings. Include also a description of study screening criteria and methodology, study quality assessment considerations, the data extraction strategy and links to any repositories/databases of relevant references.Tabular summaries and links to relevant supporting documentation are encouraged, wherever possible. More help

Evidence Supporting this KER

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help

Biological Plausibility

Addresses the biological rationale for a connection between KEupstream and KEdownstream. This field can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured. More help

A noteworthy insight, early on, was the perception that oxidation-reduction (redox) reactions in living cells are utilized in fundamental processes of redox regulation, collectively termed ‘redox signaling’ and ‘redox control’ (Sies, 2015).

Free radical-induced damage in OS has been confirmed as a contributor to the pathogenesis and patho-physiology of many chronic diseases, such as Alzheimer, atherosclerosis, Parkinson, but also in traumatic brain injury, sepsis, stroke, myocardial infraction, inflammatory diseases, cataracts and cancer (Bar-Or et al., 2015; Pisoschi and Pop, 2015). It has been assessed that oxidative stress is correlated with over 100 diseases, either as source or outcome (Pisoschi and Pop, 2015).

Therefore, the fact that ROS over-production can kill neurons is well accepted (Brown and Bal-Price, 2003; Taetzsch and Block, 2013). This ROS over-production can occur in the neurons themselves or can also have a glial origin (Yuste et al., 2015).

Empirical Evidence

Provides specific (citable) evidence that supports the idea of a change in the upstream KE (KEupstream) leading to, or being associated with, a subsequent change in the downstream KE (KEdownstream), assuming the perturbation of KEupstream is sufficient. More help

Mercury

Oxidative stress has been implicated in the pathogenesis of methylmercury (MeHg) neurotoxicity. Studies of mature neurons suggest that the mitochondrion may be a major source of MeHg-induced reactive oxygen species and a critical mediator of MeHg-induced neuronal death, likely by activation of apoptotic pathways. (Polunas et al., 2011)

(Lu et al., 2011) - MeHg in the mouse cerebrum (in vivo) and in cultured Neuro-2a cells (in vitro).

In vivo - 50µg/kg/day MeHg for 7 consecutive weeks - increased levels of lipid peroxidation in the plasma and cerebral cortex. Decreased GSH level and increase the expressions of caspase-3, -7, and -9, accompanied by Bcl-2 down-regulation and up-regulation of Bax, Bak, and p53.
In vitro – 3 and 5 µM MeHg - reduced cell viability, increased oxidative stress damage, and induced several features of mitochondria-dependent apoptotic signals, including increased sub-G1 hypodiploids, mitochondrial dysfunctions, and the activation of PARP, and caspase cascades.
These MeHg-induced apoptotic-related signals could be remarkably reversed by antioxidant NAC.

(Sarafian et al., 1994) - Hypothalamic mouse neural cell line GT1-7 without and with expression construct for the anti-apoptotic proto-oncogene, bcl-2.

3h exposure, 10 µM MeHg - increased formation of reactive ROS, and decreased levels of GSH, associated with 20% cell death. Cells transfected with an expression construct bcl-2, displayed attenuated ROS induction and negligible cell death.
24h exposure, 5 µM MeHg - killed 56% of control cells, but only 19% of bcl-2-transfected cells.
By using diethyl maleate to deplete cells of GSH, we demonstrate that the differential sensitivity to MeHg was not due solely to intrinsically different GSH levels. The data suggest that MeHg-mediated cell killing correlates more closely with ROS generation than with GSH levels and that bcl-2 protects MeHg-treated cells by suppressing ROS generation.

(Castoldi et al., 2000) - In vitro exposure of primary cultures of rat CGCs to MeHg resulted in a time- and concentration-dependent cell death.

1 hr exposure, 5–10 µM MeHg - impairment of mitochondrial activity, de-energization of mitochondria and plasma membrane lysis, resulting in necrotic cell death.
1hr exposure, 0.5–1 µM MeHg - did not compromise cell viability, mitochondrial membrane potential and function at early time points.
1hr exposure, 1 µM MeHg - only a small population of neurons (+-20%) dies by necrosis. The surviving neurons show network damage, but maintain membrane integrity, mitochondrial membrane potential and function at early time points. Later, however, the cells progressively display the morphological signs of apoptosis.
18hr exposure, 0.5–1 µM MeHg – cells progressively underwent apoptosis reaching the 100% cell death
insulin-like growth factor-I partially rescued CGCs from MeHg-triggered apoptosis.

(Kaur,et al., 2006) - primary cell cultures of cerebellar neurons and astrocytes from 7-day-old NMRI mice. 5 mM MeHg for 30 min.

Twenty-one days post-astrocyte isolation - 250mM N-acetyl cysteine (NAC) or 3mM di-ethyl maleate (DEM) added to the wells 12 h prior to MeHg exposure
7 days post-neurons isolation - 200mM of NAC or 1.8mM of DEM added to the wells 12 h prior to MeHg exposure
The intracellular GSH content was modified by pretreatment with NAC or DEM for 12 h.
Treatment with 5 mM Me Hg for 30 min led to significant (p < 0.05) increase in ROS and reduction (p < 0.001) in GSH content.
Depletion of intracellular GSH by DEM further increased the generation of MeHg-induced ROS in both cell cultures.
NAC supplementation increased intracellular GSH and provided protection against MeHg-induced oxidative stress in both cell cultures.

(Franco et al., 2007) – Mitochondrial enriched fractions from adult (2 months old) Swiss Albino male mice.

MeHg and HgCl2 (10–100 µM) significantly decreased mitochondrial viability; this phenomenon was positively correlated to mercurial-induced glutathione oxidation.
Both mercurials induced a significant reduction of GSH in a dose-dependent manner.
Correlation analyses showed significant positive correlations between mitochondrial viability and glutathione content for MeHg (Pearson coefficient) 0.933; P < 0.01) and or HgCl2 (Pearson coefficient ) 0.854; P < 0.01).
Quercetin (100–300 µM) prevented mercurial-induced disruption of mitochondrial viability. Moreover, quercetin, which did not display any chelating effect on MeHg or HgCl2, prevented mercurial-induced glutathione oxidation.

(Polunas et al., 2011) - Murine embryonal carcinoma (EC) cells, which differentiate into neurons following exposure to retinoic acid.

4h exposure, 1.5 mM MeHg - earlier and significantly higher levels of ROS production and more extensive mitochondrial depolarization in neurons than in undifferentiated EC cells. cyclosporin A (CsA) completely inhibited mitochondrial depolarization by MeHg in EC cells but only delayed this response in the neurons. In contrast, CsA significantly inhibited MeHg-induced neuronal ROS production. Cyt c release was also more extensive in neurons, with less protection afforded by CsA.

(Sandström et al., 2016) - in vitro 3D human neural tissues from neural progenitor cells derived from human embryonic stem cells. Single MeHg exposure at day 42 of 3D culturing (week 6) and material was collected 72 h after.

1-10 μM - LDH activity increased, confirming induced cell death.
5 and 10 μM - increased HMOX1 gene expression as indirect marker of oxidative stress.

Acrylamide

(Allam et al., 2011) - sixty albino Rattus norvegicus, 45 virgin females and 15 mature males. This study examined its effects on the development of external features in cubs.

prenatal intoxicated group - newborns from mothers treated with ACR (10 mg/kg/day by gastric intubation) from day 7 (GD 7) of gestation till birth
perinatal intoxicated group - newborns from mothers treated with ACR (10 mg/kg/day by gastric intubation) from GD7 of gestation till D28 after birth

ACR administered either prenatally or perinatally has been shown to induce significant retardation in the new- borns’ body weights development, increase of thiobarbituric acid- reactive substances (TBARS) and oxidative stress (significant reductions in reduced glutathione, total thiols, superoxide dismutase and peroxidase activities) in the developing cerebellum. ACR treatment delayed the proliferation in the granular layer and delayed both cell migration and differentiation. Purkinje cell loss was also seen in acrylamide-treated animals. Ultrastructural studies of Purkinje cells in the perinatal group showed microvacuolations and cell loss.

(Lakshmi et al., 2012) - Wistar male albino rats, four groups (n = 6 per group)

II – (Acrylamide) ACR - 30 mg/kg ACR for 30 days: increase in the lipid peroxidative (LPO), protein carbonyl, hydroxyl radical and hydroperoxide levels with subsequent decrease in the activities of enzymic antioxidants and level of GSH. Cortex showed condensed nuclei along with damaged cells. Decrease in the expression of Bcl2 along with simultaneous increase in the expressions of Bax and Bad as compared to control.
II rats – ACR + Fish oil -0.5 ml/kg b.w.fish oil orally 10 min before ACR induction with 30 mg/kg for 30 days – reversed significantly all the OS markers.

Uncertainties and Inconsistencies

Addresses inconsistencies or uncertainties in the relationship including the identification of experimental details that may explain apparent deviations from the expected patterns of concordance. More help

Mercury-induced upregulation of GSH level and GR activity as an adaptive mechanism following lactational exposure to methylmercury (10 mg/L in drinking water) associated with motor deficit, suggesting neuronal impairment (Franco et al., 2006).

Known modulating factors

This table captures specific information on the MF, its properties, how it affects the KER and respective references.1.) What is the modulating factor? Name the factor for which solid evidence exists that it influences this KER. Examples: age, sex, genotype, diet 2.) Details of this modulating factor. Specify which features of this MF are relevant for this KER. Examples: a specific age range or a specific biological age (defined by...); a specific gene mutation or variant, a specific nutrient (deficit or surplus); a sex-specific homone; a certain threshold value (e.g. serum levels of a chemical above...) 3.) Description of how this modulating factor affects this KER. Describe the provable modification of the KER (also quantitatively, if known). Examples: increase or decrease of the magnitude of effect (by a factor of...); change of the time-course of the effect (onset delay by...); alteration of the probability of the effect; increase or decrease of the sensitivity of the downstream effect (by a factor of...) 4.) Provision of supporting scientific evidence for an effect of this MF on this KER. Give a list of references. More help

Quantitative Understanding of the Linkage

Captures information that helps to define how much change in the upstream KE, and/or for how long, is needed to elicit a detectable and defined change in the downstream KE. More help

Reference	Chemical Concentration	OS	Cell injury/death
(Sarafian et al., 1994)	MeHg 0 µM	ROS – ±100% DCF Fluorescence GSH – ±150% MCB Fluorescence	±90% Viability
	MeHg 5 µM	ROS – ±150% DCF Fluorescence GSH – ±100% MCB Fluorescence	±80% Viability
	MeHg 10 µM	ROS – ±200% DCF Fluorescence GSH – ±70% MCB Fluorescence	±70% Viability
(Lu et al., 2011) in vitro	MeHg 0µM	(2h) ROS – ±100% DCF Fluorescence (24h) 100% intracellular GSH levels	100% Cell viability
	MeHg 3µM	(2h) ROS – ±160 DCF Fluorescence (24h) ±60% intracellular GSH levels	±50% Cell viability
	MeHg 5µM	(2h) ROS – ±230 DCF Fluorescence (24h) ±30% intracellular GSH levels	±10% Cell viability
	MeHg 3µM + NAC 1mM	(2h) ROS – ±70 DCF Fluorescence (24h) ±90% intracellular GSH levels	±90% Cell viability
	MeHg 5µM + NAC 1mM	(2h) ROS% – ±70 DCF Fluorescence (24h) ±90% intracellular GSH levels	±90% Cell viability
(Kaur et al., 2006)	0 mM MeHg	(Neurons) GSH – 100v MCB Fluorescence ROS – 100% CMH₂DCFDA Fluorescence (Astrocytes) GSH – 100v MCB Fluorescence ROS – 100% CMH₂DCFDA Fluorescence	(Neurons) 100% Cell viability (Astrocytes) 100% Cell viability
	5 mM MeHg	(Neurons) GSH – ± 50v MCB Fluorescence ROS – ± 400% CMH₂DCFDA Fluorescence (Astrocytes) GSH – ± 70% MCB Fluorescence ROS – ± 120% CMH₂DCFDA Fluorescence	(Neurons) ±60% Cell viability (Astrocytes) ±75% Cell viability
	5 mM MeHg + NAC	(Neurons) GSH – ± 80% MCB Fluorescence ROS – ± 200% CMH₂DCFDA Fluorescence (Astrocytes) GSH – ± 80% MCB Fluorescenc e ROS – ± 90% CMH₂DCFDA Fluorescence	(Neurons) ±90% Cell viability (Astrocytes) ±90% Cell viability
	5 mM MeHg + DEM	(Neurons) GSH – ± 50% MCB Fluorescenc e ROS – ± 470% CMH₂DCFDA Fluorescence (Astrocytes) GSH – ± 70% MCB Fluorescence ROS – ± 120% CMH₂DCFDA Fluorescence	(Neurons) ±55% Cell viability (Astrocytes) ±65% Cell viability
	NAC	(Neurons) GSH – ± 110v MCB Fluorescence ROS – ± 100% CMH₂DCFDA Fluorescence (Astrocytes) GSH – ±100% MCB Fluorescence ROS – ± 60% CMH₂DCFDA Fluorescence	(Neurons) ±110% Cell viability (Astrocytes) ±110% Cell viability
	DEM	(Neurons) GSH – ± 60% MCB Fluorescence ROS – ± 250% CMH₂DCFDA Fluorescence (Astrocytes) GSH – ± 80 MCB Fluorescence ROS – ± 110 CMH₂DCFDA Fluorescence	(Neurons) ±80% Cell viability (Astrocytes) ±85% Cell viability
(Franco et al., 2007)	0 µM MeHg	100% GSH	100% mitochondrial viability
	30 µM MeHg	± 70% GSH	± 70% mitochondrial viability
	0 µM HgCl₂	100% GSH	100% mitochondrial viability
	30 µM HgCl₂	± 65% GSH	± 65% mitochondrial viability
(Lakshmi et al., 2012)	Control	GSH – 0.5 µmoles/mg of protein	± 6 Damaged cells/Field
	Acrylamid	GSH – 0.2 µmoles/mg of protein	± 20 Damaged cells/Field
	Acrylamid + Fish Oil	GSH – 0.4 µmoles/mg of protein	± 11 Damaged cells/Field
	Fish Oil	GSH – 0.5 µmoles/mg of protein	± 5 Damaged cells/Field

Response-response Relationship

Provides sources of data that define the response-response relationships between the KEs. More help

Time-scale

Information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). More help

Known Feedforward/Feedback loops influencing this KER

Define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits. More help

Domain of Applicability

A free-text section of the KER description that the developers can use to explain their rationale for the taxonomic, life stage, or sex applicability structured terms. More help

Rat, Mouse: (Sarafian et al., 1994; Castoldi et al., 2000; Kaur et al., 2006; Franco et al., 2007; Lu et al., 2011; Polunas et al., 2011)

(Richetti et al., 2011) - Adult and healthy zebrafish of both sexes (12 animals and housed in 3 L) mercury chloride final concentration of 20 mg/L. Mercury chloride promoted a significant decrease in acetylcholinesterase activity and the antioxidant competence was also decreased.

(Berntssen, Aatland and Handy, 2003) - Atlantic salmon (Salmo salar L.) were supplemented with mercuric chloride (0, 10, or 100 mg Hg per kg) or methylmercury chloride (0, 5, or 10 mg Hg per kg) for 4 months.

Methylmercury chloride

accumulated significantly in the brain of fish fed 5 or 10 mg/kg
No mortality or growth reduction
- 2-fold increase in the antioxidant enzyme super oxide dismutase (SOD) in the brain
10 mg/kg - 7-fold increase of lipid peroxidative products (thiobarbituric acid reactive substances, TBARS) and a subsequently 1.5-fold decrease in anti oxidant enzyme activity (SOD and glutathione peroxidase, GSH-Px). Fish also had pathological damage (vacoulation and necrosis), significantly reduced neural enzyme activity (5-fold reduced monoamine oxidase, MAO, activity), and reduced overall post-feeding activity behaviour.

Mercuric chloride

accumulated significantly in the brain only at 100 mg/kg
No mortality or growth reduction
100 mg/kg - significant reduced neural MAO activity and pathological changes (astrocyte proliferation) in the brain, however, neural SOD and GSH-Px enzyme activity, lipid peroxidative products (TBARS), and post feeding behaviour did not differ from controls.

References

List of the literature that was cited for this KER description. More help

Allam, a et al. (2011) ‘Prenatal and perinatal acrylamide disrupts the development of cerebellum in rat: Biochemical and morphological studies.’, Toxicology and industrial health, 27, pp. 291–306. doi: 10.1177/0748233710386412.

Bar-Or, D. et al. (2015) ‘Oxidative stress in severe acute illness’, Redox Biology. Elsevier, 4, pp. 340–345. doi: 10.1016/j.redox.2015.01.006.

Berntssen, M. H. G., Aatland, A. and Handy, R. D. (2003) ‘Chronic dietary mercury exposure causes oxidative stress, brain lesions, and altered behaviour in Atlantic salmon (Salmo salar) parr’, Aquatic Toxicology, 65(1), pp. 55–72. doi: 10.1016/S0166-445X(03)00104-8.

Bhandari, R. and Kuhad, A. (2015) ‘Neuropsychopharmacotherapeutic efficacy of curcumin in experimental paradigm of autism spectrum disorders’, Life Sciences. Elsevier Inc., 141, pp. 156–169. doi: 10.1016/j.lfs.2015.09.012.

Brown, G.C. and Bal-Price, A. (2003) ‘Inflammatory neurodegeneration mediated by nitric oxide, glutamate, and mitochondria’, Molecular Biology, 27(3), pp. 325-355.

Castoldi, A. F. et al. (2000) ‘Early acute necrosis, delayed apoptosis and cytoskeletal breakdown in cultured cerebellar granule neurons exposed to methylmercury’, Journal of Neuroscience Research, 59(6), pp. 775–787. doi: 10.1002/(SICI)1097-4547(20000315)59:6<775::AID-JNR10>3.0.CO;2-T.

Coyle, J. and Puttfarcken, P. (1993) ‘Glutamate Toxicity’, Science, 262, pp. 689–95.

Franco, J. L. et al. (2006) ‘Cerebellar thiol status and motor deficit after lactational exposure to methylmercury’, Environmental Research, 102(1), pp. 22–28. doi: 10.1016/j.envres.2006.02.003.

Franco, J. L. et al. (2007) ‘Mercurial-induced hydrogen peroxide generation in mouse brain mitochondria: Protective effects of quercetin’, Chemical Research in Toxicology, 20(12), pp. 1919–1926. doi: 10.1021/tx7002323.

Gilgun-Sherki, Y., Melamed, E. and Offen, D. (2001) ‘Oxidative stress induced-neurodegenerative diseases: The need for antioxidants that penetrate the blood brain barrier’, Neuropharmacology, 40(8), pp. 959–975. doi: 10.1016/S0028-3908(01)00019-3.

Grandjean, P. and Landrigan, P. J. (2014) ‘Neurobehavioural effects of developmental toxicity’, The Lancet Neurology, 13(3), pp. 330–338. doi: 10.1016/S1474-4422(13)70278-3.

Kaur, P., Aschner, M. and Syversen, T. (2006) ‘Glutathione modulation influences methyl mercury induced neurotoxicity in primary cell cultures of neurons and astrocytes’, NeuroToxicology, 27(4), pp. 492–500. doi: 10.1016/j.neuro.2006.01.010.

Lakshmi, D. et al. (2012) ‘Ameliorating effect of fish oil on acrylamide induced oxidative stress and neuronal apoptosis in cerebral cortex’, Neurochemical Research, 37(9), pp. 1859–1867. doi: 10.1007/s11064-012-0794-1.

Lu, T. H. et al. (2011) ‘Involvement of oxidative stress-mediated ERK1/2 and p38 activation regulated mitochondria-dependent apoptotic signals in methylmercury-induced neuronal cell injury’, Toxicology Letters. Elsevier Ireland Ltd, 204(1), pp. 71–80. doi: 10.1016/j.toxlet.2011.04.013.

Madhavan, L. et al. (2006) ‘Increased "vigilance" of antioxidant mechanisms in neural stem cells potentiates their capability to resist oxidative stress’, Stem Cells 24(2) pp. 2110-2119.

Markesbery, W. R. (1997) ‘Oxidative stress hypothesis in Alzheimer’s disease’, Free Radical Biology and Medicine, 23(1), pp. 134–147. doi: 10.1016/S0891-5849(96)00629-6.

Pisoschi, A. M. and Pop, A. (2015) ‘The role of antioxidants in the chemistry of oxidative stress: A review’, European Journal of Medicinal Chemistry. Elsevier Masson SAS, 97, pp. 55–74. doi: 10.1016/j.ejmech.2015.04.040.

Polunas, M. et al. (2011) ‘Role of oxidative stress and the mitochondrial permeability transition in methylmercury cytotoxicity’, NeuroToxicology. Elsevier B.V., 32(5), pp. 526–534. doi: 10.1016/j.neuro.2011.07.006.

Reynolds, A. et al. (2007) ‘Oxidative Stress and the Pathogenesis of Neurodegenerative Disorders’, International Review of Neurobiology, 82(7), pp. 297–325. doi: 10.1016/S0074-7742(07)82016-2.

Richetti, S. K. et al. (2011) ‘Acetylcholinesterase activity and antioxidant capacity of zebrafish brain is altered by heavy metal exposure’, NeuroToxicology. Elsevier B.V., 32(1), pp. 116–122. doi: 10.1016/j.neuro.2010.11.001.

Rossignol, D. A. and Frye, R. E. (2014) ‘Evidence linking oxidative stress, mitochondrial dysfunction, and inflammation in the brain of individuals with autism’, Frontiers in Physiology, 5 APR(April), pp. 1–15. doi: 10.3389/fphys.2014.00150.

Sandström, J. et al. (2016) ‘Toxicology in Vitro Development and characterization of a human embryonic stem cell-derived 3D neural tissue model for neurotoxicity testing’, Tiv, pp. 1–12. doi: 10.1016/j.tiv.2016.10.001.

Sandström, J. et al. (2017) ‘Potential mechanisms of development-dependent adverse effects of the herbicide paraquat in 3D rat brain cell cultures’, NeuroToxicology, 60, pp. 116–124. doi: 10.1016/j.neuro.2017.04.010.

Sarafian, T. A. et al. (1994) ‘Bcl-2 Expression Decreases Methyle Mercury-Induced Free-Radical Generation and Cell Killing in a Neural Cell Line’, Toxicol. Lett., 74(2), pp. 149–155.

Sies, H. (2015) ‘Oxidative stress: A concept in redox biology and medicine’, Redox Biology. Elsevier, 4, pp. 180–183. doi: 10.1016/j.redox.2015.01.002.

Taetzsch, T. and Block, M.L. (2013) ‘Pesticides, microglial NOX2, and Parkinson's disease’, J Biochem Molecular Toxicology, 27(2), pp. 137-149.

Wang, X. and Michaelis, E. K. (2010) ‘Selective neuronal vulnerability to oxidative stress in the brain’, Frontiers in Aging Neuroscience, 2(MAR), pp. 1–13. doi: 10.3389/fnagi.2010.00012.

Wells, P. G. et al. (2009) ‘Oxidative stress in developmental origins of disease: Teratogenesis, neurodevelopmental deficits, and cancer’, Toxicological Sciences, 108(1), pp. 4–18. doi: 10.1093/toxsci/kfn263.

Yuste, J.E., et al., 2015. Implications of glial nitric oxide in neurodegenerative diseases. Front Cell Neurosci. 9, 322.