Inhibit, serotonin transporter activity

GO:0005576

GO extracellular region

CHEBI:28790

CHEBI serotonin

PR:000011406

PR glucocorticoid receptor

CHEBI:29108

CHEBI calcium(2+)

MP:0010069

MP increased serotonin level

GO:0004883

GO glucocorticoid receptor activity

VT:0010499

VT calcium amount

WIKI increased

SSRI (Selective serotonin reuptake inhibitor)

2017-04-13T15:32:43

Increase cortisone levels (induced by stress)

2017-04-14T14:34:24

2017-06-01T11:16:42

WikiUser_26

ApacheUser rodents

WikiUser_6

ApacheUser fish

WCS_9606

common toxicological species human

10116

NCBI rat

10090

NCBI mouse

WikiUser_28

Vertebrates

10116

NCBI Rattus norvegicus

9606

NCBI Homo sapiens

Inhibit, serotonin transporter activity

Molecular

AOPWiki 2017-04-13T14:16:49

2017-04-13T14:16:49

Decreased, serotonin transporter activity

Molecular

AOPWiki 2017-04-13T14:17:16

2017-05-31T16:47:44

Decreased, extracellular sodium (Na+)

Decreased, extracellular Na+

Molecular

AOPWiki 2017-04-13T14:18:45

2017-04-13T14:18:45

Decreased, extracellular chloride (Cl-)

Molecular

AOPWiki 2017-04-13T14:19:23

2017-04-13T14:19:23

Increased, extracellular serotonin

Molecular

Extracellular serotonin levels are determined by a balance between the synthesis from tryptophan in cells, release into the synaptic cleft, reuptake into cells by serotonin reuptake transporter (SERT; 5-hydroxytryptamine transporter; 5-HTT), and breakdown to 5-hydroxindile acetic acid (5-HIAA) (Conde et al. 2023).  Selective serotonin reuptake inhibitor (SSRI) antidepressants are a class of compounds known to inhibit serotonin reuptake transporter activity and increase extracellular serotonin levels (McDonald 2017).

Serotonin concentrations can be measured via microdialysis/high-performance liquid chromatography, fast-scan cyclic voltammetry, N-Shaped Multiple Cyclic Square Wave Voltammetry, and Fast-Scan Controlled-Adsorption Voltammetry (Rojas Cabrera et al. 2023).

Life Stage: Applies to all life stages with developed brain and central nervous systems. Sex: Applies to both males and females. Taxonomic: Primarily studied in laboratory rodents, humans, and fish.  Serotonin is present in diverse taxa from bacteria to plants to animals (Goncalves et al. 2022).

High Unspecific

Moderate

All life stages

High High

Conde, K., Fang, S. and Xu, Y. 2023.  Unraveling the serotonin saga: from discovery to weight regulation and beyond - a comprehensive scientific review. Cell and Bioscience 13: 143. Goncalves, S., Nunes-Costa, D.N., Cardoso, S.M., Empadinhas, N., and Marugg, J.D.  2022.  Enzyme Promiscuity in Serotonin Biosynthesis, From Bacteria to Plants and Humans.  Frontiers in Microbiology 13: 873555. McDonald, M.D.  2017.  An AOP analysis of selective serotonin reuptake inhibitors (SSRIs) for fish. Comparative Biochemistry and Physiology, Part C-Toxicology and Pharmacology 197: 19–31. Rojas Cabrera, J.M., Oesterle, T.S., Rusheen, A.E., Goyal, A., Scheitler, K.M., Mandybur, I., Blaha, C.D., Bennet, K.E., Heien, M.L., Jang, D.P., Lee, K.H., Oh, Y., and Shin, H. 2023. Techniques for Measurement of Serotonin: Implications in Neuropsychiatric Disorders and Advances in Absolute Value Recording Methods. ACS Chemical Neuroscience 14(24): 4264-4273. NOTE: Italics indicate edits from John Frisch January 2025.   AOPWiki 2017-04-13T14:20:14

2025-02-13T14:30:44

Increased, intracellular sodium (Na+)

Molecular

AOPWiki 2017-04-13T14:21:05

2017-04-13T14:21:05

Increased, intracellular chloride (Cl-)

Molecular

AOPWiki 2017-04-13T14:21:34

2017-04-13T14:21:34

Decreased, intracellular serotonin

Molecular

AOPWiki 2017-04-13T14:47:41

2017-05-31T16:47:24

Decreased, packaged serotonin

Molecular

AOPWiki 2017-04-13T14:48:44

2017-05-31T16:46:49

Decreased, synaptic release

Molecular

AOPWiki 2017-04-13T14:49:20

2017-05-31T16:46:28

Increased, 5-HT3 (5-hydroxytryptamine)

Increased, 5-HT3

Molecular

AOPWiki 2017-04-13T14:57:01

2017-06-01T14:48:51

Inactivated, 5-HTR (serotonin receptors)

Inactivated, 5-HTR

Molecular

AOPWiki 2017-04-13T14:59:07

2017-05-31T16:45:48

Reduce expression, BDNF (Brain-derived neurotrophic factor)

Reduce expression, BDNF

Molecular

AOPWiki 2017-04-13T15:00:03

2017-05-31T16:40:41

Decreased, neuroplasticity

Molecular

<ul> <li>Neuroplasticity, also known as synaptic or brain plasticity, is a mechanism by which the brain undergoes structural and functional changes. It is defined as the brain’s ability to modify its activity in response to extrinsic and intrinsic stimuli, enabling the reorganization of its structure and function — for example, following brain injury. (Puderbaugh et al; 2023)</li> <li>The biochemical processes that occur and are associated with synapses and other components of the brain form the foundation of neuroplasticity. These processes involve both functional and structural changes in the brain, enabling adaptation to the environment, learning, memory formation, and rehabilitation following brain injury. (Gulyaeva 2017)</li> <li> Basically, neuroplasticity can be defined primarily as the modification of the structure or function of the nervous system in response to environmental changes. (Stee & Peigneux, 2021) </li> <li> Synaptic plasticity is time-dependent. (Johson et al; 2023)  </li> <li> It is suggested that neuroplasticity is also associated with neurogenesis. (Stee et al., 2021) </li> <li> Recently, neuroplastic changes have also been found in the thickness of the myelin sheath and in the diameter of the axon. (Fields, 2015; Xin e Chan, 2020; Tramblay et al., 2021)  </li> <li> Although the initial description of neuroplasticity focused solely on the brain, it actually occurs throughout the entire central nervous system. (Liu & Chambers, 1958) </li> <li> In basic research, it has been observed that chronic stress leads to impaired neuroplasticity, resulting in neuronal atrophy and synaptic loss in the medial prefrontal cortex (mPFC) and the hippocampus. Structural alterations and changes in specific neural circuits are associated with performance deficits observed in depressed patients during cognitive and neuropsychological tasks. Such deficits are consistent with a reduced ability to interact flexibly with stimuli and to engage in goal-directed cognition efficiently. (Price & Duman, 2020) </li> </ul>

The main approaches to detect and measure the reduction of neural plasticity include: Biochemical and protein markers: altered levels of brain-derived neurotrophic factor (BDNF) are associated with impaired synaptic plasticity, as well as imbalances between excitatory and inhibitory neuronal signaling. (Sarriés-Serrano et al., 2025)  Neuroimaging or electrophysiological techniques: studies using EEG or fMRI can identify structural and functional changes that may reflect reduced synaptic plasticity. (Herzberg et al., 2024) Animal models demonstrating reduced synaptic activity: for instance, studies have shown that dopamine depletion induces alterations in hippocampal synaptic plasticity in mice. (Kim et al., 2023) Behavioral and cognitive/neuropsychological performance assays: deficits in tasks requiring cognitive effort, learning, or memory may indicate altered neuroplasticity and serve as an indirect measurement method.  Use of indirect biomarkers: peripheral biomarkers, such as those found in blood or saliva, can also serve as indicators of changes related to brain plasticity. (Mougeot et al., 2016)

Neuroplasticity is well characterized in vertebrates. Animal models such as rats and mice are well established as tools for studying neural plasticity. More recently, zebrafish (Danio rerio) have also been used as an experimental model to investigate neuroplasticity. (De Jager et al., 2024; Hall & Tropepe, 2018., Calvo‑Ochoa & Byrd‑Jacobs, 2019)

UBERON:0000955

UBERON brain

CL:0002319

CL neural cell

High Mixed

High

During brain development, adulthood and aging

High High High Puderbaugh, M. and P. D. Emmady (2023), Neuroplasticity, Hennepin Healthcare and UNC School of Medicine, Atrium Health, last updated 1 May 2023.  Gulyaeva, N. V. (2017). Molecular mechanisms of neuroplasticity: An expanding universe. Biochemistry (Moscow), 82(3), 237–245. https://doi.org/10.1134/S0006297917030014  Stee, W., & Peigneux. (2021). Post-learning micro- and macro-structural neuroplasticity changes with time and sleep. Biochemical Pharmacology, 191, 114369. https://doi.org/10.1016/j.bcp.2020.114369  Fields, R.D. (2015). A new mechanism of nervous system plasticity: activity-dependent myelination. Nature Reviews Neuroscience, 16(12), 756–767. https://doi.org/10.1038/nrn4023  Xin, W., & Chan, J.R. (2020). Myelin plasticity: sculpting circuits in learning and memory. Nature Reviews Neuroscience, 21, 682–694. https://doi.org/10.1038/s41583-020-00379-8  Tremblay, S.A., Jäger, A.-T., Huck, J., Giacosa, C., Beram, S., Schneider, U., Grahl, S., Villringer, A., Tardif, C.L., Bazin, P.-L., Steele, C.J., & Gauthier, C.J. (2021). White matter microstructural changes in short-term learning of a continuous visuomotor sequence. Brain Structure and Function, 226, 2061–2077. https://doi.org/10.1007/s00429-021-02267-y  Liu, C.N., & Chambers, W.W. (1958). Intraspinal sprouting of dorsal root axons: development of new collaterals and preterminals following partial denervation of the spinal cord in the cat. AMA Archives of Neurology and Psychiatry, 79(1), 46–61. https://doi.org/10.1001/archneurpsyc.1958.02340010050005  Price, R.B., & Duman, R. (2020). Neuroplasticity in cognitive and psychological mechanisms of depression: an integrative model. Molecular Psychiatry, 25, 530–543. https://doi.org/10.1038/s41380-019-0615-x Sarriés-Serrano, U., Miquel-Rio, L., Santana, N., Paz, V., Sancho-Alonso, M., Callado, L.F., Meana, J.J., & Bortolozzi, A. (2025). Impaired unfolded protein response, BDNF and synuclein markers in the dorsolateral prefrontal cortex and caudate nucleus postmortem of patients with depression and Parkinson’s disease. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 128, 111299. https://doi.org/10.1016/j.pnpbp.2025.111299  Herzberg, M.P., Nielsen, A.N., Luby, J., & Sylvester, C.M. (2024). Measuring neuroplasticity in human development: the potential to guide the type and timing of mental health interventions. Neuropsychopharmacology. Published online August 5, 2024. https://doi.org/10.1038/s41386-024-01947-7  Kim, B., Kim, J.-S., Youn, B., & Changjong, L. (2023). Dopamine depletion alters neuroplasticity-related signaling in the rat hippocampus. Experimental Neurobiology, 32(6), 557–567. https://doi.org/10.1080/19768354.2023.2294308  Mougeot, J.-L.C., Hirsch, M.A., Stevens, C.B., & Mougeot, F.K.B. (2016). Oral biomarkers in exercise-induced neuroplasticity in Parkinson’s disease. Oral Diseases, 22(8), 745–753. https://doi.org/10.1111/odi.12463  De Jager, J.E., Boesjes, R., Roelandt, G.H.J., Koliaki, I., Sommer, Í.E.C., Schoevers, R.A., & Nuninga, J.O. (2024). Shared effects of electroconvulsive shocks and ketamine on neuroplasticity: a systematic review of animal models of depression. Neuroscience & Biobehavioral Reviews, (105796). https://doi.org/10.1016/j.neubiorev.2024.105796  Hall, Z.J., & Tropepe, V. (2018). Movement maintains forebrain neurogenesis via peripheral neural feedback in larval zebrafish. eLife, 7, e31045. https://doi.org/10.7554/eLife.31045  Calvo‑Ochoa, E., & Byrd‑Jacobs, C.A. (2019). The olfactory system of zebrafish as a model for the study of neurotoxicity and injury: implications for neuroplasticity and disease. International Journal of Molecular Sciences, 20(7), 1639. https://doi.org/10.3390/ijms20071639  AOPWiki 2017-04-13T15:09:18

2025-11-10T15:27:33

Increase, cortisone

Molecular

AOPWiki 2017-04-13T15:14:07

2017-04-13T15:14:07

Increase, Glucocorticoid receptor activation

Increase, GR activation

Molecular

Site of action:  The molecular site of action is the glucocorticoid receptor (GR), nuclear receptor part of a superfamily of highly conserved which bind to steroids, sterols, thyroid hormones, retinoids, and orphan receptors (Weikum et al., 2017). In humans, the formal gene name of this receptor is nuclear receptor subfamily 3, group C, member 1 – NR3C1 (Oakley & Cidlowski, 2013). More specifically, the GR agonism occurs through the interaction of a chemical (endogenous compounds such as cortisol, or an external stressor) with the ligand binding domain. In the absence of a ligand, the GR is transcriptionally inactive in the cytoplasm (Barnes, 1998). Responses at the macromolecular level:  Once bound to a hormonal ligand, the GR is translocated from the cytoplasm to the nucleus where the activated GR interacts with genomic glucocorticoid-response elements (GRE) and regulates transcription of associated genes. Interactions with double stranded DNA and transcription factors can cause both activation and repression of downstream genes via directly binding to a consensus site, binding to other transcription factors to form a heterodimer, or homodimerization prior to DNA binding (Oakley & Cidlowski, 2013).

Glucocorticoid receptor activation can be measured via bioanalytical tools such as in vitro bioassays where results are typically reported in Dexamethasone-equivalents (DEX-EQ) . However it should be noted that these assays have differences in sensitivity (Cole & Brooks, 2023).             <table border="1" cellpadding="1" cellspacing="1" style="width:500px"> <caption>In Vitro Assays Employed in Glucocorticoid Receptor Agonism Detection</caption> <tbody> <tr> <td>Assay</td> <td>Receptor Organism</td> <td>Tissue</td> <td>Citation</td> </tr> <tr> <td> TOX21 GR BLA Agonist Ratio </td> <td>Human</td> <td>Cervix</td> <td>Huang et al., 2011</td> </tr> <tr> <td>GR CALUX</td> <td>Human</td> <td>Osteosarcoma</td> <td>Been et al., 2021; Macikova et al., 2014; Schriks et al., 2010; Suzuki et al., 2015</td> </tr> <tr> <td>Attagene GR TRANS</td> <td>Human</td> <td>Liver</td> <td>Martin et al., 2010; Medvedev et al., 2018; Romanov et al., 2008</td> </tr> <tr> <td>Attagene GRe CIS</td> <td>Human</td> <td>Liver</td> <td>Martin et al., 2010; Medvedev et al., 2018; Romanov et al., 2008</td> </tr> <tr> <td>CV1-hGR</td> <td>Human</td> <td>Kidney</td> <td>Medlock Kakaley et al., 2019</td> </tr> <tr> <td>GR-GeneBlazer</td> <td>Human</td> <td>Kidney</td> <td>Jia et al., 2016</td> </tr> <tr> <td>NovaScreen NR hGR</td> <td>Human</td> <td>N/A</td> <td>Knudsen et al., 2011; Sipes et al., 2013</td> </tr> <tr> <td>Trout GR1</td> <td>Trout</td> <td>Kidney</td> <td>Kugathas & Sumpter, 2011</td> </tr> <tr> <td>Trout GR2</td> <td>Trout</td> <td>Kidney</td> <td>Kugathas & Sumpter, 2011</td> </tr> <tr> <td>Indigo hGR</td> <td>Human</td> <td>N/A</td> <td>Cavaillin et al., 2021; Cole et al., 2025</td> </tr> <tr> <td>Indigo zfGR</td> <td>Zebrafish</td> <td>N/A</td> <td>Cole et al., 2025</td> </tr> </tbody> </table>   In addition to bioanalytical techniques, induction of GR-regulated genes are also indicative of GR agonism in vivo (Cavallin et al., 2021; Cole et al., 2025; Garland et al., 2019).

Taxonomic Applicability: The GR is present in almost every vertebrate cell (Weikum et al., 2017). The evolutionary conservation of GR activation across taxa was examined in silico through the employment of EPA’s Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) Tool, and 623 orthologs were identified confirming conservation in vertebrate species. Additionally, bioanalytical methods comparing zebrafish (Danio rerio) GR and human GR show conservation of ligand binding and receptor agonism when using dexamethasone and beclomethasone dipropionate. Lastly, the fathead minnow (Pimephales promelas) model has been employed to examine susceptibility to synthetic glucocorticoids in the following in vivo exposure to dexamethasone and beclomethasone dipropionate (Cole et al., 2025). Through the processes of gene duplication and divergence, the GR and mineralocorticoid receptor (MR) evolved from a corticoid receptor in jawless fish. While only possessing one isoform of MR, teleost fish possess two isoforms of the GR and all three have affinity for endogenous cortisol (Baker et al., 2013). Conservation of susceptibility does not infer similarities in sensitivity which varies based on species, receptor isoform, and tissue (Aedo et al., 2023; Baker et al., 2013; Bury & Sturm, 2007; Gilmour, 2005; Jerez-Cepa et al., 2019; Small & Quiniou, 2018; Stolte et al., 2006) <img alt="Results from (A) Level 1 Sequence Alignment to Predict Cross-Species Susceptibility (SeqAPASS) comparing 1,631 protein sequences to zebrafish glucocorticoid receptor (zfGR). Analysis resulted in 782 ortholog candidates at a susceptibility cut-off of 20.55%. (B) Level 2 SeqAPASS analysis examining the ligand binding domain (LDB) of zfGR which resulted in 784 orthologs at a susceptibility cut-off of 34.47%." src="https://aopwiki.org/system/dragonfly/production/2025/04/18/9oyje58ylm_image_5_.png" style="height:1745px; width:1505px" /> Figure: Results from (A) Level 1 Sequence Alignment to Predict Cross-Species Susceptibility (SeqAPASS) comparing 1,631 protein sequences to zebrafish glucocorticoid receptor (zfGR). Analysis resulted in 782 ortholog candidates at a susceptibility cut-off of 20.55%. (B) Level 2 SeqAPASS analysis examining the ligand binding domain (LDB) of zfGR which resulted in 784 orthologs at a susceptibility cut-off of 34.47%.   Life Stage Applicability: This MIE is not life stage specific. However, the downstream transcriptional effects of GR agonism may vary based on life stage. (LaLone et al., 2012; Watanabe et al., 2016).   Sex Applicability: This MIE is not sex specific.

CL:0000255

CL eukaryotic cell

High Unspecific

Moderate

All life stages

High

Aedo, J. E., Zuloaga, R., Aravena-Canales, D., Molina, A., & Valdés, J. A. (2023). Role of glucocorticoid and mineralocorticoid receptors in rainbow trout (Oncorhynchus mykiss) skeletal muscle: A transcriptomic perspective of cortisol action. Frontiers in Physiology, 13, 1048008. https://doi.org/10.3389/fphys.2022.1048008 Baker, M. E., Funder, J. W., & Kattoula, S. R. (2013). Evolution of hormone selectivity in glucocorticoid and mineralocorticoid receptors. The Journal of Steroid Biochemistry and Molecular Biology, 137, 57–70. Barnes, P. J. (1998). Anti-inflammatory actions of glucocorticoids: Molecular mechanisms. Clinical Science (London, England: 1979), 94(6), 557–572. https://doi.org/10.1042/cs0940557 Been, F., Pronk, T., Louisse, J., Houtman, C., van der Velden-Slootweg, T., van der Oost, R., & Dingemans, M. M. L. (2021). Development of a framework to derive effect-based trigger values to interpret CALUX data for drinking water quality. Water Research, 193. https://doi.org/10.1016/j.watres.2021.116859 Bury, N. R., & Sturm, A. (2007). Evolution of the corticosteroid receptor signalling pathway in fish. General and Comparative Endocrinology, 153(1), 47–56. https://doi.org/10.1016/j.ygcen.2007.03.009 Cavallin, J. E., Battaglin, W. A., Beihoffer, J., Blackwell, B. R., Bradley, P. M., Cole, A. R., Ekman, D. R., Hofer, R. N., Kinsey, J., Keteles, K., Weissinger, R., Winkelman, D. L., & Villeneuve, D. L. (2021). Effects-Based Monitoring of Bioactive Chemicals Discharged to the Colorado River before and after a Municipal Wastewater Treatment Plant Replacement. Environmental Science & Technology, 55(2), 974–984. https://doi.org/10.1021/acs.est.0c05269 Cole, A. R., & Brooks, B. W. (2023). Comparative Endpoint Sensitivity of Bioanalytical Tools for Glucocorticoid Receptor Agonism Surveillance in Aquatic Matrices. ACS ES&T Water, 3(9), 3082–3092. <a href="https://doi.org/10.1021/acsestwater.3c00253">https://doi.org/10.1021/acsestwater.3c00253</a> Cole, A. R., Blackwell, B. R., Cavallin, J. E., Collins, J. E., Kittelson, A. R., Shmaitelly, Y. M., Langan, L. M., Villenueve, D. L., & Brooks, B. W. (2025). Comparative Glucocorticoid Receptor Agonism: In Silico, In Vitro, and In Vivo and Identification of Potential Biomarkers for Synthetic Glucocorticoid Exposure. Environmental Toxicology and Chemistry, vgae041. https://doi.org/10.1093/etojnl/vgae041 Garland, M. A., Sengupta, S., Mathew, L. K., Truong, L., de Jong, E., Piersma, A. H., La Du, J., & Tanguay, R. L. (2019). Glucocorticoid receptor-dependent induction of cripto-1 (one-eyed pinhead) inhibits zebrafish caudal fin regeneration. Toxicology Reports, 6, 529–537. https://doi.org/10.1016/j.toxrep.2019.05.013 Gilmour, K. M. (2005). Mineralocorticoid receptors and hormones: Fishing for answers. Endocrinology, 146(1), 44–46. Huang, R., Xia, M., Cho, M.-H., Sakamuru, S., Shinn, P., Houck, K. A., Dix, D. J., Judson, R. S., Witt, K. L., Kavlock, R. J., Tice, R. R., & Austin, C. P. (2011). Chemical Genomics Profiling of Environmental Chemical Modulation of Human Nuclear Receptors. Environmental Health Perspectives, 119(8), 1142–1148. https://doi.org/10.1289/ehp.1002952 Jerez-Cepa, I., Gorissen, M., Mancera, J. M., & Ruiz-Jarabo, I. (2019). What can we learn from glucocorticoid administration in fish? Effects of cortisol and dexamethasone on intermediary metabolism of gilthead seabream (Sparus aurata L.). Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology, 231, 1–10. https://doi.org/10.1016/j.cbpa.2019.01.010 Jia, A., Wu, S., Daniels, K. D., & Snyder, S. A. (2016). Balancing the Budget: Accounting for Glucocorticoid Bioactivity and Fate during Water Treatment. Environmental Science & Technology, 50(6), 2870–2880. https://doi.org/10.1021/acs.est.5b04893 Knudsen, T. B., Houck, K. A., Sipes, N. S., Singh, A. V., Judson, R. S., Martin, M. T., Weissman, A., Kleinstreuer, N. C., Mortensen, H. M., Reif, D. M., Rabinowitz, J. R., Setzer, R. W., Richard, A. M., Dix, D. J., & Kavlock, R. J. (2011). Activity profiles of 309 ToxCastTM chemicals evaluated across 292 biochemical targets. Toxicology, 282(1), 1–15. https://doi.org/10.1016/j.tox.2010.12.010 Kugathas, S., & Sumpter, J. P. (2011). Synthetic Glucocorticoids in the Environment: First Results on Their Potential Impacts on Fish. Environmental Science & Technology, 45(6), 2377–2383. https://doi.org/10.1021/es104105e LaLone, C. A., Villeneuve, D. L., Olmstead, A. W., Medlock, E. K., Kahl, M. D., Jensen, K. M., Durhan, E. J., Makynen, E. A., Blanksma, C. A., Cavallin, J. E., Thomas, L. M., Seidl, S. M., Skolness, S. Y., Wehmas, L. C., Johnson, R. D., & Ankley, G. T. (2012). Effects of a glucocorticoid receptor agonist, dexamethasone, on fathead minnow reproduction, growth, and development. Environmental Toxicology and Chemistry, 31(3), 611–622. https://doi.org/10.1002/etc.1729 Macikova, P., Groh, K. J., Ammann, A. A., Schirmer, K., & Suter, M. J.-F. (2014). Endocrine Disrupting Compounds Affecting Corticosteroid Signaling Pathways in Czech and Swiss Waters: Potential Impact on Fish. Environmental Science & Technology, 48(21), 12902–12911. https://doi.org/10.1021/es502711c Martin, M. T., Dix, D. J., Judson, R. S., Kavlock, R. J., Reif, D. M., Richard, A. M., Rotroff, D. M., Romanov, S., Medvedev, A., Poltoratskaya, N., Gambarian, M., Moeser, M., Makarov, S. S., & Houck, K. A. (2010). Impact of Environmental Chemicals on Key Transcription Regulators and Correlation to Toxicity End Points within EPA’s ToxCast Program. Chemical Research in Toxicology, 23(3), 578–590. https://doi.org/10.1021/tx900325g Medlock Kakaley, E., Cardon, M. C., Gray, L. E., Hartig, P. C., & Wilson, V. S. (2019). Generalized Concentration Addition Model Predicts Glucocorticoid Activity Bioassay Responses to Environmentally Detected Receptor-Ligand Mixtures. Toxicological Sciences, 168(1), 252–263. https://doi.org/10.1093/toxsci/kfy290 Medvedev, A., Moeser, M., Medvedeva, L., Martsen, E., Granick, A., Raines, L., Zeng, M., Makarov, S., Houck, K. A., & Makarov, S. S. (2018). Evaluating biological activity of compounds by transcription factor activity profiling. Science Advances, 4(9), eaar4666. https://doi.org/10.1126/sciadv.aar4666 Oakley, R. H., & Cidlowski, J. A. (2013). The Biology of the Glucocorticoid Receptor: New Signaling Mechanisms in Health and Disease. The Journal of Allergy and Clinical Immunology, 132(5), 1033–1044. https://doi.org/10.1016/j.jaci.2013.09.007 Romanov, S., Medvedev, A., Gambarian, M., Poltoratskaya, N., Moeser, M., Medvedeva, L., Gambarian, M., Diatchenko, L., & Makarov, S. (2008). Homogeneous reporter system enables quantitative functional assessment of multiple transcription factors. Nature Methods, 5(3), 253–260. https://doi.org/10.1038/nmeth.1186 Schriks, M., van Leerdam, J. A., van der Linden, S. C., van der Burg, B., van Wezel, A. P., & de Voogt, P. (2010). High-Resolution Mass Spectrometric Identification and Quantification of Glucocorticoid Compounds in Various Wastewaters in The Netherlands. Environmental Science & Technology, 44(12), 4766–4774. https://doi.org/10.1021/es100013x Sipes, N. S., Martin, M. T., Kothiya, P., Reif, D. M., Judson, R. S., Richard, A. M., Houck, K. A., Dix, D. J., Kavlock, R. J., & Knudsen, T. B. (2013). Profiling 976 ToxCast Chemicals across 331 Enzymatic and Receptor Signaling Assays. Chemical Research in Toxicology, 26(6), 878–895. https://doi.org/10.1021/tx400021f Small, B. C., & Quiniou, S. M. A. (2018). Characterization of two channel catfish, Ictalurus punctatus, glucocorticoid receptors and expression following an acute stressor. Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology, 216, 42–51. https://doi.org/10.1016/j.cbpa.2017.11.011 Stolte, E. H., Kemenade, B. M. L. V. van, Savelkoul, H. F. J., & Flik, G. (2006). Evolution of glucocorticoid receptors with different glucocorticoid sensitivity. Journal of Endocrinology, 190(1), 17–28. https://doi.org/10.1677/joe.1.06703 Suzuki, G., Sato, K., Isobe, T., Takigami, H., Brouwer, A., & Nakayama, K. (2015). Detection of glucocorticoid receptor agonists in effluents from sewage treatment plants in Japan. Science of The Total Environment, 527–528, 328–334. https://doi.org/10.1016/j.scitotenv.2015.05.008 Watanabe, Y., Grommen, S. V. H., & De Groef, B. (2016). Corticotropin-releasing hormone: Mediator of vertebrate life stage transitions? General and Comparative Endocrinology, 228, 60–68. https://doi.org/10.1016/j.ygcen.2016.02.012 Weikum, E. R., Knuesel, M. T., Ortlund, E. A., & Yamamoto, K. R. (2017). Glucocorticoid receptor control of transcription: Precision and plasticity via allostery. Nature Reviews Molecular Cell Biology, 18(3), 159–174. https://doi.org/10.1038/nrm.2016.152   AOPWiki 2016-11-29T18:41:22

2026-02-12T07:24:33

Reduced, BDNF (Brain-derived neurotrophic factor)

Reduced, BDNF

Molecular

<ul> <li>The brain-derived neurotrophic factor (BDNF) is synthesized and secreted by excitatory neurons. It is a key regulator involved in synaptic plasticity and fundamental brain processes such as cognition and memory (Barde, 2025).</li> <li>BDNF belongs to the neurotrophin family and is present throughout the central nervous system (CNS), both during development and in the mature brain. Experiments conducted with rodents have shown that postnatal expression in the prefrontal cortex is low and gradually increases as the brain matures. Therefore, it becomes evident that BDNF levels reach maturity in parallel with the maturation of cortical brain areas (Cohen-Cory et al., 2010).</li> <li>The first step in the entire process involving this neurotrophin is its synthesis and secretion. Both its expression and synthesis depend on tightly regulated mechanisms, which primarily reflect the regulation of its gene. This mechanism is essential to ensure the availability and functional activity of BDNF in specific cellular locations (Tongiorgi et al., 2006).</li> <li>The BDNF gene consists of alternatively organized exons, and its structure varies among species. For example, there are ten exons in humans, eight in rodents, and six in lower vertebrates, with only a single exon capable of fully encoding the pro-BDNF protein. The expression of the BDNF gene can be controlled by different types of promoters, which function independently depending on development, tissue type, and cellular activity. Moreover, the organization of the BDNF gene is highly conserved between fish and mammals (Aid et al., 2007; Tao et al., 2002; Rattiner et al., 2004; Kidane et al., 2009; Heirinch et al., 2004; Pruunsild et al., 2007).</li> <li>BDNF secretion occurs through two pathways: constitutive and regulated. Constitutive secretion mainly occurs in the soma, while the regulated pathway predominates in distal neuronal processes. Efficient targeting of BDNF to the regulated secretory pathway depends primarily on a specific region within the pro-domain of BDNF (Brigadiski et al., 2005).</li> <li>The following diagram illustrates the general process of activation, regulation of synthesis, and secretion of BDNF at pre- and postsynaptic sites. Presynaptic activity induces the activation of postsynaptic NMDA (N-methyl-D-aspartate) and AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) receptors. Locally produced BDNF mRNA is transported to the dendritic spine, where it is translated into protein and directed to the postsynaptic site in an activity-dependent manner. This BDNF binds to presynaptic TrkB receptors, activating intracellular signaling pathways that influence the activity of the GTPases RhoA, Rac, and Cdc42, which in turn modify actin structure through the cytoskeleton. Rac and Cdc42 act as positive regulators of cell growth and also play essential roles in neuronal branching. Additionally, BDNF can act in an autocrine manner through the activation of postsynaptic TrkB receptors (Cory et al., 2011).</li> <li>Scientific evidence shows that BDNF activation through its TrkB receptor can promote the morphological development of neurons and is also associated with synaptic connectivity (Huang & Reichardt et al., 2001; Poo et al., 2001; Zweifel et al., 2005).</li> </ul>

<ul> <li>BDNF can be measured in human serum using the enzyme-linked immunosorbent assay (ELISA) technique. (Naegelin et al; 2018); </li> <li>To measure or detect BDNF, various methods can be employed, including molecular biology techniques, immunohistochemistry, and other approaches such as immunohistochemical staining, quantitative real-time polymerase chain reaction (qPCR), and Western blot analysis (Ding et al., 2017); </li> <li>Commercially available kits utilizing sandwich enzyme-linked immunosorbent assay (ELISA) techniques have been developed to detect BDNF in cerebrospinal fluid using specific antibodies. Moreover, multiplex immunobead-based assays are employed for high-throughput and targeted screening of BDNF levels. (Trajkvska et al, 2007; Zhang et al., 2008); </li> <li> In the commercial market, a variety of assay kits are available for detecting and quantifying BDNF levels in different biological fluids, including whole blood, plasma, and platelets. (Trajkovska et al., 2007).  </li> <li> Certain precautions should be considered when measuring or detecting BDNF in plasma or serum using the ELISA method. A specific study that measured BDNF concentrations in mouse and porcine serum reported that BDNF was undetectable using this methodological approach. (Elfving et al., 2010; Klein et al., 2011)  </li> </ul>

<ul> <li>Brain-derived neurotrophic factor (BDNF) is associated with essential and fundamental brain processes in most vertebrates. Its empirical relationship with mammals has been well documented. Previous studies have investigated the determination of BDNF in whole blood, serum, plasma, and brain tissue. In one of these studies, BDNF concentrations were measured in three different mammalian species — rat, pig, and mouse — using the ELISA method. As mentioned earlier, other research groups have also demonstrated the quantification of BDNF in human serum. (Klein et al., 2011; Aid et al., 2007; Trajkovska et al. 2007). </li> <li> The role of BDNF can be observed in the brain development of fish, where it regulates cell proliferation; in birds, where it is involved in specific brain regions controlling song production; and in the visual system of Xenopus, where BDNF functions as a neurotrophic factor mediating synaptic differentiation. (Sanchez et al., 2006; Marshak et al., 2007; Brenowitz, 2013;  <a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=D%27Angelo%20L%5BAuthor%5D&cauthor=true&cauthor_uid=23983038" style="box-sizing:border-box; color:#337ab7; text-decoration:none; background-color:#ffffff; font-family:-apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji"; font-size:16px; font-style:normal; font-variant-ligatures:normal; font-weight:400; text-align:left; white-space:normal">D'Angelo L</a> et al., 2014; Heinrich e Pagtakhan, 2004).  </li> </ul>

UBERON:0000955

UBERON brain

CL:0002319

CL neural cell

High Unspecific

High

During brain development

High High High Aid, T., Kazantseva, A., Piirsoo, M., Palm, K. and Timmusk, T. (2007). Revisiting the structure and expression of the BDNF gene in mice and rats. Journal of Neuroscience Research, 85(3): 525–535. DOI: 10.1002/jnr.21139. PMID: 17149751. PMCID: PMC1878509.  Barde YA (2024). A fisiopatologia do fator neurotrófico derivado do cérebro. Revisões Fisiológicas. DOI:10.1152/physrev.00038.2024 Brenowitz EA. (2013) Testosterone and brain-derived neurotrophic factor interactions in the avian song control system. Neuroscience 239: 115-123.  Brigadski, T., Hartmann, M. and Lessmann, V. (2005). Differential vesicular targeting and time course of synaptic secretion of the mammalian neurotrophins. Journal of Neuroscience, 25(33): 7601–7614. PMID: 16107647. PMCID: PMC6725410.  Cohen-Cory, S., Kidane, AH, Shirkey, NJ, & Marshak, S. (2010). Fator neurotrófico derivado do cérebro e o desenvolvimento da conectividade neuronal estrutural . Neurobiologia do Desenvolvimento, 70 (5), 271–288. https://doi.org/10.1002/dneu.20774  Cowan, W. M., Jessell, T. M. and Zipursky, S. L. (2001). Neurotrophins as synaptic modulators. Nature Reviews Neuroscience, 2(1): 24–32. DOI: 10.1038/35049004. PMID: 11253356.  <a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=D%27Angelo%20L%5BAuthor%5D&cauthor=true&cauthor_uid=23983038">D'Angelo L</a>, <a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=De%20Girolamo%20P%5BAuthor%5D&cauthor=true&cauthor_uid=23983038">De Girolamo P</a>, <a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=Lucini%20C%5BAuthor%5D&cauthor=true&cauthor_uid=23983038">Lucini C</a>, <a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=Terzibasi%20ET%5BAuthor%5D&cauthor=true&cauthor_uid=23983038">Terzibasi ET</a>, <a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=Baumgart%20M%5BAuthor%5D&cauthor=true&cauthor_uid=23983038">Baumgart M</a>, <a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=Castaldo%20L%5BAuthor%5D&cauthor=true&cauthor_uid=23983038">Castaldo L</a>, <a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=Cellerino%20A%5BAuthor%5D&cauthor=true&cauthor_uid=23983038">Cellerino A</a> (2014). Brain-derived neurotrophic factor: mRNA expression and protein distribution in the brain of the teleost Nothobranchius furzeri. <a href="https://www.ncbi.nlm.nih.gov/pubmed/23983038" title="The Journal of comparative neurology.">J Comp Neurol.</a> 1;522(5):1004-30.  Ding, S., T. Zhu, Y. Tian, P. Xu, Z. Chen, X. Huang and X. M. Zhang (2017), Role of brain-derived neurotrophic factor in endometriosis pain, Reproductive Sciences, https://doi.org/10.1177/1933719117732161  Elfving B, Plougmann PH, Wegener G. (2010) Detecção do fator neurotrófico derivado do cérebro (BDNF) em sangue de rato e preparações cerebrais usando ELISA: dificuldades e soluções. J Neurosci Methods 187: 73-77.  Heinrich, G. and Pagtakhan, C. J. (2004). Both 5′ and 3′ flanks regulate zebrafish brain-derived neurotrophic factor gene expression. BMC Neuroscience, 5: 19. DOI: 10.1186/1471-2202-5-19. PMID: 15153250. PMCID: PMC442124.  Huang and Reichardt (2001) – Neurotrophins: roles in neuronal development and function. Annu. Rev. Neurosci. 24: 677–736. PMID: 11520916. PMCID: PMC2758233.  Kidane, A. H., Heinrich, G., Dirks, R. P. H., de Ruyck, B. A., Lubsen, N. H., Roubos, E. W. and Jenks, B. G. (2009). Differential neuroendocrine expression of multiple brain-derived neurotrophic factor transcripts. Endocrinology, 150(4): 1361–1371. DOI: 10.1210/en.2008-0993. PMID: 19008311.  Klein AB, Williamson R, Santini MA, Clemmensen C, Ettrup A, Rios M, Knudsen GM, Aznar S. (2011) As concentrações de BDNF no sangue refletem os níveis de BDNF no tecido cerebral em diferentes espécies. Int J Neuropsychopharmacol. 14: 347-353. Marshak S, Nikolakopoulou AM, Dirks R, Martens GJ, Cohen-Cory S (2007)Cell-autonomous TrkB signaling in presynaptic retinal ganglion cells mediates axon arbor growth and synapse maturation during the establishment of retinotectal synaptic connectivity. J Neurosci 27:2444 –2456.  Naegelin, Y., H. Dingsdale, K. Säuberli, S. Schädelin, L. Kappos and Y.-A. Barde (2018), Measurement and validation of brain-derived neurotrophic factor (BDNF) levels in human serum, eNeuro, Vol. 5, No. 2, Article ENEURO.0419-17.2018, <a href="https://doi.org/10.1523/ENEURO.0419-17.2018" target="_new">https://doi.org/10.1523/ENEURO.0419-17.2018</a>  Pruunsild et al. (2007) – Dissecting the human BDNF locus: Bidirectional transcription, complex splicing, and multiple promoters. Gene 394(1–2): 1–13. PMID: 17629449. PMCID: PMC2568880.  Rattiner, L. M., Davis, M., French, C. T. and Ressler, K. J. (2004). Brain-derived neurotrophic factor and tyrosine kinase receptor B involvement in amygdala-dependent fear conditioning. Journal of Neuroscience, 24(20): 4796–4806. DOI: 10.1523/JNEUROSCI.5654-03.2004. PMID: 15152040. PMCID: PMC6729469. Sanchez AL, Matthews BJ, Meynard MM, Hu B, Javed S, Cohen Cory S (2006) BDNF increases synapse density in dendrites of developing tectal neurons in vivo. Development 133:2477–2486.  Tongiorgi, E., Domenici, L. e Simonato, M. (2006). Qual é o significado biológico do direcionamento do mRNA do BDNF nos dendritos? Indícios da epilepsia e do desenvolvimento cortical. Neurobiologia Molecular , 33(1), 17–32. DOI: 10.1385/MN:33:1:017  Trajkovska V, Marcussen AB, Vinberg M, Hartvig P, Aznar S, Knudsen GM. (2007) Measurements of brain-derived neurotrophic factor: methodological aspects and demographical data. Brain Res Bull. 73: 143-149. Xu, T., West, A. E., Chen, W. G., Corfas, G. and Greenberg, M. E. (2001). A calcium-responsive transcription factor, CaRF, that regulates neuronal activity-dependent expression of BDNF. Neuron, 33(3): 383–395. DOI: 10.1016/S0896-6273(01)00561-X. PMID: 11832226.  Zhang J, Sokal I, Peskind ER, Quinn JF, Jankovic J, Kenney C, Chung KA, Millard SP, Nutt JG, Montine TJ. (2008) CSF multianalyte profile distinguishes Alzheimer and Parkinson diseases. Am J Clin Pathol. 129: 526-529. Zweifel, L. S., Kuruvilla, R. and Ginty, D. D. (2005). Functions and mechanisms of retrograde neurotrophin signalling. Nature Reviews Neuroscience, 6(8): 615–625. DOI: 10.1038/nrn1727. PMID: 16062170.      AOPWiki 2017-04-13T15:15:22

2025-11-10T11:08:12

Activation, 5-HT2A (Serotonin 2A)

Activation, 5-HT2A

Molecular

AOPWiki 2017-04-13T15:25:34

2017-04-13T15:25:34

Activate, PLC (Phospholipase C)

Activate, PLC

Molecular

AOPWiki 2017-04-13T15:26:24

2017-04-13T15:26:24

Increase, inositol triphosphate

Molecular

AOPWiki 2017-04-13T15:27:05

2017-04-13T15:27:05

Increase, intracellular calcium

Cellular

Calcium is arguably the most versatile and important intracellular messenger in neurons (Berridge et al., 2000). Interestingly, although calcium may often promote neuronal death, it can also activate pathways that promote survival. For example, calcium can promote survival through a pathway involving activation of protein kinase B (PKB/Akt) by calcium/calmodulin-dependent protein kinase (Yano et al., 1998). Calcium is a prominent regulator of cellular responses to stress, activating transcription through the cyclic-AMP response element-binding protein (CREB), which can promote neuron survival in experimental models of developmental cell death (Hu et al., 1999). Calcium can also activate a rapid neuroprotective signalling pathway in which the calcium-activated actin-severing protein gelsolin induces actin depolymerization, resulting in suppression of calcium influx through membrane NMDA (N-methyl-d-aspartate) receptors and voltage-dependent calcium channels (Furukawa et al., 1997). This may occur through intermediary actin-binding proteins that interact with NMDA receptor and calcium channel proteins. Finally, signals such as calcium and secreted amyloid precursor protein-α (sAPP-α), which increase cyclic GMP production, can induce activation of potassium channels and the transcription factor NF-κB, and thereby increase resistance of neurons to excitotoxic apoptosis (Furukawa et al., 1996).

An increase in [Ca2+]i was measured using Fluo3 AM as an indicator dye after the addition of metals (single or in mixture) to the culture wells following an optimized protocol (Arey et al., 2022). The fluorescent signals were read by fluorescence imaging plate reader Synergy HT (BioTek, Winooski, VT) (Rai and others 2010). Briefly, Ca2+ levels in human astrocytes were monitored by fluorescence microscopy using the Ca2+ indicator fluo-4. Slices were incubated with fluo-4-AM (2–5 µL of 2 mM dye were dropped over the tissue, attaining a final concentration of 2–10 µM and 0.01% of pluronic) and Sulforhodamine 101 (100 µM) for 30–60 min at room temperature (Navarrete and others 2013). In these conditions, most of the Fluo-4-loaded cells were astrocytes as indicated by their SR101 staining (Nimmerjahn et al., 2004; Dombeck et al., 2007; Kafitz et al., 2008; Takata and Hirase 2008), and confirmed in some cases by their electrophysiological properties. Astrocytes were imaged with an Olympus FV300 laser-scanning confocal microscope or a CCD camera (Retiga EX) attached to the Olympus BX50WI microscope (Navarrete and others 2013). Diversity of endogenous Ca2+ activity in a mature hippocampal astrocyte in situ: Ca2+ signals in cell body and processes are different. (A) Cumulative Ca2+ activity recorded in an astrocyte over a 165 s period revealed by the calcium indicator Fluo4-AM. The visible boundaries of the astrocyte are shown in white. Note the different intensities of spatially- confined local activity in the astrocyte cell body (s), primary process (p1) stemming from the soma and secondary processes (p2) branching from a primary process. Intensity of the normalized cumulative activity is expressed in arbitrary units (a.u.) and shown in pseudocolour, from dark (lowest) to white (highest). (B) Frequency map of the Ca2+ activity in the astrocyte during the 165 s period as in A. Activity is measured in individual pixels, expressed in mHz and color-coded from black (never active) to dark red (frequently active). Most of the activity is within the white boundaries and the most frequently active pixels are in defined small regions (arrowheads) of the primary and secondary processes (30 mHz), whereas pixels of the soma are less active (~10 mHz) (Volterra et al., 2014).  Free intracellular calcium ions were measured using the fluorescent calcium indicator FLUO-3/AM (Molecular probes, Eugene, OR, USA). Cells (4 × 104 cells/cm2) were seeded in 24-well plates for 24 h to reach 60%–70%, and then treated for 24 h with As(III) (0.5 and 1 mg/l), or coexposed to As(III) (1 mg/l) and F (2.5, 5, and 10 mg/l). After treatment, supernatant was collected and combined with trypsinized cells. Pelleted samples were resuspended in 500 μl of FLUO-3/AM (4 μmol/l) and incubated at 37 °C for 30 min. After centrifugation, cells were washed with HBSS (Hank's Buffered Salt Solution, Sigma), made up to 400 μl with HBSS and analyzed by flow cytometry. The signal from FLUO-3/AM bound to Ca2+ was recorded using the Fl-1 channel (Rocha et al., 2011). Fluo-4/AM was used as an intracellular free Ca2+ fluorescent probe to analyze [Ca2+]i in Cd-exposed cerebral cortical neurons. In short, the harvested cells were incubated with Fluo-4/AM (5 µmol/L final concentration) for 30 min at 37°C in the dark, washed with PBS, and analyzed on a BD-FACS Aria flow cytometry. Intracellular [Ca2+]i levels were represented by fluorescent intensity. Fluorescent intensity was recorded by excitation at 494 nm and emission at 516 nm. The data were analyzed by Cell Quest program (Becton Dickinson), and the mean fluorescence intensity was obtained by histogram statistics (Yuan et al., 2013).

UBERON:0000955

UBERON brain

CL:0000000

CL cell

Moderate Mixed

Moderate

Adult, reproductively mature

Moderate

Birth to < 1 month

Moderate Moderate

Arey BJ Seethala R Ma Z Fura A Morin J Swartz J Vyas V Yang W Dickson JK JrFeyen JH A novel calcium-sensing receptor antagonist transiently stimulates parathyroid hormone secretion in vivo Endocrinology 2005 146 2015 2022 Asit Rai and others, Characterization of Developmental Neurotoxicity of As, Cd, and Pb Mixture: Synergistic Action of Metal Mixture in Glial and Neuronal Functions, Toxicological Sciences, Volume 118, Issue 2, December 2010, Pages 586–601, https://doi.org/10.1093/toxsci/kfq266 Berridge, M. J., Lipp, P. & Bootman, M. D. The versatility and universality of calcium signaling. Nature Rev. Mol. Cell Biol. 1, 11– 21 (2000). Dombeck DA, Khabbaz AN, Collman F, Adelman TL, Tank DW. Imaging large-scale neural activity with cellular resolution in awake, mobile mice, Neuron, 2007, vol. 56 (pg. 43-57) Furukawa, K. et al. The actin-severing protein gelsolin modulates calcium channel and NMDA receptor activities and vulnerability to excitotoxicity in hippocampal neurons. J. Neurosci. 17, 8178– 8186 (1997). Furukawa, K., Barger, S. W., Blalock, E. M. & Mattson, M. P. Activation of K+ channels and suppression of neuronal activity by secreted β-amyloid-precursor protein. Nature 379, 74–78 (1996). Hu, S. C., Chrivia, J. & Ghosh, A. Regulation of CBP-mediated transcription by neuronal calcium signaling. Neuron 22, 799– 808 (1999). Kafitz KW, Meier SD, Stephan J, Rose CR. Developmental profile and properties of sulforhodamine 101-labeled glial cells in acute brain slices of rat hippocampus, J Neurosci Methods, 2008, vol. 169 (pg. 84-92) Marta Navarrete and others, Astrocyte Calcium Signal and Gliotransmission in Human Brain Tissue, Cerebral Cortex, Volume 23, Issue 5, May 2013, Pages 1240–1246, https://doi.org/10.1093/cercor/bhs122 Nimmerjahn A, Kirchhoff F, Kerr JN, Helmchen F. Sulforhodamine 101 as a specific marker of astroglia in the neocortex in vivo, Nat Methods, 2004, vol. 1 (pg. 31-37) R.A. Rocha, J.V. Gimeno-Alcañiz, R. Martín-Ibañez, J.M. Canals, D. Vélez, V. Devesa, Arsenic and fluoride induce neural progenitor cell apoptosis, Toxicology Letters, Volume 203, Issue 3, 2011, Pages 237-244, ISSN 0378-4274, https://doi.org/10.1016/j.toxlet.2011.03.023. Takata N, Hirase H. Cortical layer 1 and layer 2/3 astrocytes exhibit distinct calcium dynamics in vivo., PLoS ONE, 2008, vol. 3 pg. e2525 Volterra, Andrea, Nicolas Liaudet, and Iaroslav Savtchouk. "Astrocyte Ca2+ signalling: an unexpected complexity." Nature Reviews Neuroscience 15.5 (2014): 327-335. Yano, S., Tokumitsu, H. & Soderling, T. R. Calcium promotes cell survival through CaM-K kinase activation of the protein-kinase-B pathway. Nature 396, 584–587 (1998). Yuan Y, Jiang C-y, Xu H, Sun Y, Hu F-f, Bian J-c, et al. (2013) Cadmium-Induced Apoptosis in Primary Rat Cerebral Cortical Neurons Culture Is Mediated by a Calcium Signaling Pathway. PLoS ONE 8(5): e64330. https://doi.org/10.1371/journal.pone.0064330 AOPWiki 2017-04-13T15:27:51

2023-07-21T16:26:34

Activate, calmodulin

Molecular

AOPWiki 2017-04-13T15:28:30

2017-04-13T15:28:30

Increase, myosin light chain phosphorylation

Molecular

AOPWiki 2017-04-13T15:29:22

2017-04-13T15:29:22

Increase, vascular smooth muscle contraction

Molecular

AOPWiki 2017-04-13T15:30:06

2017-04-13T15:30:06

Increased, seizure

Individual

AOPWiki 2017-04-13T15:35:33

2017-06-01T11:55:50

Increased, agitation

Molecular

AOPWiki 2017-04-13T15:36:15

2017-06-01T11:35:55

Increased, depression

Individual

<ul> <li>Depression usually manifests initially with physical symptoms, such as physical fatigue and sleep disturbances. A depressed mood may also be present. Therapy, in combination with pharmacological treatment, has positive effects when used together, more so than when they are used in isolation. (RE Rakel., 1999); Depression can affect not only one’s own health, but also relationships and cognitive performance, such as learning. As demonstrated, there is significant relevance surrounding depression, since data show a mortality risk higher than that associated with smoking. The lifetime incidence of a depressive episode is 17% in the United States and 13% in Europe. The analysis and interpretation of these data indicate that there is a need for, and relevance of, research addressing this disease (Bitsika et al., 2010; Mykletun et al., 2009; Alonso et al., 2004; Kessier et al., 1994)  Depression is common; however, it is serious. It is characterized by a depressed mood, loss of interest in activities previously performed by the individual, an abnormal reduction in energy, and a considerable increase in the risk of suicide. (Malhi e Mann, 2018). According to the DSM-5 classification, there are other types of depression, which include: persistent depressive disorder (previously called dysthymia); disruptive mood dysregulation disorder; premenstrual dysphoric disorder; substance/medication-induced depressive disorder; depressive disorder due to another medical condition; and unspecified depressive disorder (Bains et al., 2023). </li> <li> The causes that lead to the development of depression are multifactorial, involving genetic factors as well as environmental factors that influence the onset of this mental disorder. First-degree relatives of individuals with depression have a threefold higher probability of developing the disorder compared to the general population. It is important to note that depression can also affect individuals without a family history of the disease. In addition to genetic factors, there are other factors that may trigger depression, particularly biological ones. These include neurodegenerative diseases, especially Alzheimer’s and Parkinson’s disease; stroke; multiple sclerosis; seizure disorders; cancer; macular degeneration; and chronic pain, all of which are also associated with depression (Chand et al., 2023; Pham et al., 2019; Namkung et al., 2019).  </li> <li> The pathophysiology related to depressive disorder is associated with evidence of a neurochemical imbalance among the neurotransmitters serotonin (5-HT), norepinephrine (NE), dopamine (DA), and glutamate, as well as Brain-Derived Neurotrophic Factor (BDNF) (Chand et al., 2023)  </li> </ul>

Depression can be measured or detected through assessments conducted with standardized interviews and specific scoring, as well as through biological markers and brain imaging. Depression can be detected, classified, and also measured through specific questionnaires standardized by the DSM-5, such as the Hamilton Depression Rating Scale (HAM-D), Beck Depression Inventory (BDI), and Patient Health Questionnaire-9 (PHQ-9). Molecular biomarkers are also excellent tools that may assist in detecting depression, such as alterations in serotonin, dopamine, and norepinephrine levels; dysfunction of the HPA axis (cortisol measurement); and measurement of brain-derived neurotrophic factor (BDNF) (Stockings et al., 2015; Costa et al., 2016; Boby et al., 2025., Malik et al., 2021)

The increase in depression shows high applicability in mammals, particularly in humans and rodents. Its relevance to other vertebrates is also considerable and biologically plausible (Crawley et al., 2022; Houk et al., 2025).

High Unspecific

High

All life stages

High High High <ul> <li> Kessler, R.C., McGonagle, K.A., Zhao, S., et al. (1994), Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States: Results from the National Comorbidity Survey, Archives of General Psychiatry, 51(1): 8-19, http://dx.doi.org/10.1001/archpsyc.1994.03950010008002. </li> <li> Alonso, J., Angermeyer, M.C., Bernert, S., Bruffaerts, R., Brugha, T.S., Bryson, H. et al. (2004), Prevalence of mental disorders in Europe: results from the European Study of the Epidemiology of Mental Disorders (ESEMeD) project, Acta Psychiatrica Scandinavica. Supplementum, 109(420): 21-27, http://dx.doi.org/10.1111/j.1600-0047.2004.00327.x. </li> <li> Mykletun, A., Bjerkeset, O., Øverland, S., Prince, M., Dewey, M., Stewart, R. (2009), Levels of anxiety and depression as predictors of mortality: the HUNT study, British Journal of Psychiatry, 195: 118-125, http://dx.doi.org/10.1192/bjp.bp.108.054866. </li> <li> Sharpley, C.F. & Bitsika, V. (2010), Joining the dots: neurobiological links in a functional analysis of depression, Behavioral and Brain Functions, 6: 73, http://dx.doi.org/10.1186/1744-9081-6-73 </li> <li> Rakel, R.E. (1999), Depression, Primary Care: Clinics in Office Practice, 26(2): 211-224, http://dx.doi.org/10.1016/S0095-4543(08)70003-4  </li> <li> Malhi, G.S. & Mann, J.J. (2018), Depression, The Lancet, 392(10161): 2299-2312, http://dx.doi.org/10.1016/S0140-6736(18)31948-2  </li> <li> American Psychiatric Association (2013), Diagnostic and Statistical Manual of Mental Disorders: DSM-5, 5th ed., American Psychiatric Publishing, Washington, DC </li> <li> Bains, N. and S. Abdijadid (2023), Major Depressive Disorder, in StatPearls [Internet], StatPearls Publishing, Treasure Island (FL). Disponível em: <a href="https://www.ncbi.nlm.nih.gov/books/NBK559078/" rel="noopener" target="_new">https://www.ncbi.nlm.nih.gov/books/NBK559078/</a>  </li> <li> Chand, S.P. and H. Arif (2023), Depression, in StatPearls [Internet], StatPearls Publishing, Treasure Island (FL). Disponível em: <a href="https://www.ncbi.nlm.nih.gov/books/NBK430847/" rel="noopener" target="_new">https://www.ncbi.nlm.nih.gov/books/NBK430847/</a>  </li> <li> Kennis, M.; Gerritsen, L.; van Dalen, M.; Williams, A.; Cuijpers, P.; Bockting, C. (2015). Prospective biomarkers of major depressive disorder: A systematic review and meta-analysis. Molecular Psychiatry. Disponível em: <a href="https://pubmed.ncbi.nlm.nih.gov/25553406/?utm_source=chatgpt.com" rel="noopener" target="_new">https://pubmed.ncbi.nlm.nih.gov/25553406/</a>  </li> <li> Lopresti, A. L.; Hood, S. D.; Drummond, P. D. (2016). A review of peripheral biomarkers in major depression: The potential of inflammatory and neurotrophic markers. Progress in Neuro-Psychopharmacology & Biological Psychiatry. Disponível em: <a href="https://pubmed.ncbi.nlm.nih.gov/27304758/?utm_source=chatgpt.com" rel="noopener" target="_new">https://pubmed.ncbi.nlm.nih.gov/27304758/</a>  </li> <li> (Autores do artigo ScienceDirect). (2024). Depression diagnosis: EEG-based cognitive biomarkers and machine learning. Neuroscience & Biobehavioral Reviews. Disponível em: <a href="https://www.sciencedirect.com/science/article/abs/pii/S0166432824004819?utm_source=chatgpt.com" rel="noopener" target="_new">https://www.sciencedirect.com/science/article/abs/pii/S0166432824004819</a>  </li> <li> Gadad, B. S.; Jha, M. K.; Czysz, A. H.; et al. (2021). Biomarkers of Major Depressive Disorder: Knowing is Half the Battle. International Journal of Molecular Sciences. Disponível em: <a href="https://pubmed.ncbi.nlm.nih.gov/33508785/?utm_source=chatgpt.com" rel="noopener" target="_new">https://pubmed.ncbi.nlm.nih.gov/33508785/</a>  </li> <li> Houk, J.; et al. From rodents to humans: conserved codistribution of dopaminergic with serotonergic neurons in the dorsal raphe nucleus. ScienceDirect, 2025. Disponível em: <a href="https://www.sciencedirect.com/science/article/pii/S0969996125003900" rel="noopener" target="_new">https://www.sciencedirect.com/science/article/pii/S0969996125003900</a>  </li> <li> Crawley, J. N.; et al. Introducing a depression-like syndrome for translational neuropsychiatry: a plea for taxonomical validity and improved comparability between humans and mice. Molecular Psychiatry, 2022. Disponível em: <a href="https://www.nature.com/articles/s41380-022-01762-w" rel="noopener" target="_new">https://www.nature.com/articles/s41380-022-01762-w</a>  </li> </ul> AOPWiki 2017-04-13T15:36:41

2026-02-06T13:22:02

Increase, hypertension

Individual

AOPWiki 2017-04-13T15:30:37

2017-04-13T15:30:37

Decreased, extracellular serotonin

Molecular

AOPWiki 2017-04-14T14:38:23

2017-05-31T16:46:08

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AOPWiki 2017-04-14T14:44:31

2017-04-14T14:44:31

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AOPWiki 2017-04-14T14:45:05

2017-04-14T14:45:05

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AOPWiki 2017-04-14T14:45:47

2017-04-14T14:45:47

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AOPWiki 2017-04-14T14:46:05

2017-04-14T14:46:05

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AOPWiki 2017-04-14T14:46:40

2017-04-14T14:46:40

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AOPWiki 2017-04-14T14:47:11

2017-04-14T14:47:11

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AOPWiki 2017-04-14T14:47:31

2017-04-14T14:47:31

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AOPWiki 2017-04-14T14:47:56

2017-04-14T14:47:56

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AOPWiki 2017-04-14T14:48:43

2017-04-14T14:48:43

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AOPWiki 2017-04-14T14:49:08

2017-04-14T14:49:08

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AOPWiki 2017-04-14T14:49:24

2017-04-14T14:49:24

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AOPWiki 2017-04-14T14:49:42

2017-04-14T14:49:42

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AOPWiki 2017-04-14T14:50:01

2017-04-14T14:50:01

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AOPWiki 2017-04-14T14:50:24

2017-04-14T14:50:24

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AOPWiki 2017-04-14T14:50:38

2017-04-14T14:50:38

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AOPWiki 2017-04-14T14:51:06

2017-04-14T14:51:06

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AOPWiki 2017-04-14T14:51:25

2017-04-14T14:51:25

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AOPWiki 2017-04-14T14:51:51

2017-04-14T14:51:51

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AOPWiki 2017-04-14T14:52:12

2017-04-14T14:52:12

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AOPWiki 2017-04-14T14:52:36

2017-04-14T14:52:36

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AOPWiki 2017-04-14T14:53:03

2017-04-14T14:53:03

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AOPWiki 2017-04-14T14:53:31

2017-04-14T14:53:31

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AOPWiki 2017-04-14T14:54:04

2017-04-14T14:54:04

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AOPWiki 2017-04-14T14:54:31

2017-04-14T14:54:31

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AOPWiki 2017-04-14T14:55:00

2017-04-14T14:55:00

<upstream-id>5298c900-5799-4695-ad3e-76ff8a9b6c98</upstream-id> <downstream-id>a10f8db5-3f19-4fa9-8481-e3b0f29af722</downstream-id>

AOPWiki 2017-04-14T14:55:18

2017-04-14T14:55:18

Network of SSRIs (selective serotonin reuptake inhibitors)

Network of SSRIs

Lyle Burgoon

Open for adoption

1.0

The increase in depression is associated with high suicide rates and a significant socioeconomic impact.

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AOPWiki 2017-04-13T14:11:48

2023-04-29T16:03:00