Cited by 12

Revolutionizing developmental neurotoxicity testing - a journey from animal models to advanced in vitro systems

·2024·ALTEX

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.14573/altex.2403281

Cites

8 of 8 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 134

  1. Algharably EA, Di Consiglio E, Testai E (2023). Predi.ction of in vivo prenatal chlorpyrifos exposure leading to developmental neurotoxicity in humans based on in vitro toxicity data by quantitative in vitro-in vivo extrapolation. Front Pharmacol 14, 1136174. doi: 10.3389/fphar.2023.1136174 36959852 PMC10027916 · DOI
  2. Ankley GT, Bennett RS, Erickson RJ (2010). Adverse outcome pathways: A conceptual framework to support ecotoxicology research and risk assessment. Environ Toxicol Chem 29, 730– 741. doi: 10.1002/etc.34 20821501 · DOI · Paper page
  3. Arts JHE, Faulhammer F, Schneider S (2023). Investigations on learning and memory function in extended one-generation reproductive toxicity studies – When considered needed and based on what? Crit Rev Toxicol 53, 372– 384. doi: 10.1080/10408444.2023.2236134 37540214 · DOI
  4. Arzuaga X, Smith MT, Gibbons CF (2019). Proposed key characteristics of male reproductive toxicants as an approach for organizing and evaluating mechanistic evidence in human health hazard assessments. Environ Health Perspect 127, 065001. doi: 10.1289/ehp5045 31199676 PMC6792367 · DOI
  5. Aschner M, Ceccatelli S, Daneshian M (2017). Selection of reference compounds for characterization and development of alternative methods for developmental neurotoxicity (DNT) testing. ALTEX 34, 49– 74. doi: 10.14573/altex.1604201 27452664 PMC5250586 · DOI
  6. Bal-Price A, Hogberg HT, Buzanska L (2010). In vitro developmental neurotoxicity (DNT) testing: Relevant models and endpoints. Neurotoxicology 31, 545– 554. doi: 10.1016/j.neuro.2009.11.006 19969020 · DOI
  7. Bal-Price AK, Coecke S, Costa L (2012). Advancing the science of developmental neurotoxicity (DNT): Testing for better safety evaluation. ALTEX 29, 202– 215. doi: 10.14573/altex.2012.2.202 22892558 · DOI
  8. Bal-Price A, Crofton KM, Sachana M (2015a). Putative adverse outcome pathways relevant to neurotoxicity. Crit Rev Toxicol 45, 83– 91. doi: 10.3109/10408444.2014.981331 25605028 PMC5072123 · DOI · Paper page
  9. Bal-Price A, Crofton KM, Leist M (2015b). International STakeholder NETwork (ISTNET): Creating a developmental neurotoxicity (DNT) testing road map for regulatory purposes. Arch Toxicol 89, 269– 287. doi: 10.1007/s00204-015-1464-2 25618548 PMC4309915 · DOI
  10. Bal-Price A and Meek ME (2017). Adverse outcome pathways: Application to enhance mechanistic understanding of neurotoxicity. Pharmacol Ther 179, 84– 95. doi: 10.1016/j.pharmthera.2017.05.006 28529068 PMC5869951 · DOI
  11. Bal-Price A, Hogberg HT, Crofton KM (2018a). t4 workshop report: Recommendation on test readiness criteria for new approach methods in toxicology: Exemplified for developmental neurotoxicity. ALTEX 35, 306– 352. doi: 10.14573/altex.1712081 29485663 PMC6545888 · DOI
  12. Bal-Price A, Pistollato F, Sachana M (2018b). Strategies to improve the regulatory assessment of developmental neurotoxicity (DNT) using in vitro methods. Toxicol Appl Pharmacol 354, 7– 18. doi: 10.1016/j.taap.2018.02.008 29476865 PMC6095942 · DOI
  13. Basketter DA, Clewell H, Kimber I, (2012). A roadmap for the development of alternative (non-animal) methods for systemic toxicity testing. ALTEX 29, 3– 89. doi: 10.14573/altex.2012.1.003 22307314 · DOI
  14. Baumann J, Gassmann K, Masjosthusmann S (2016). Comparative human and rat neurospheres reveal species differences in chemical effects on neurodevelopmental key events. Arch Toxicol 90, 1415– 1427. doi: 10.1007/s00204-015-1568-8 26216354 · DOI · Paper page
  15. Bellanger M, Demeneix BA, Grandjean P (2015). Neurobehavioral deficits, diseases, and associated costs of exposure to endocrine-disrupting chemicals in the European Union. J Clin Endocrinol Metab 100, 1256– 1266. doi: 10.1210/jc.2014-4323 25742515 PMC4399309 · DOI
  16. Blaauboer BJ, Boekelheide K, Clewell HJ (2012). The use of biomarkers of toxicity for integrating in vitro hazard estimates into risk assessment for humans. ALTEX 29, 411– 425. doi: 10.14573/altex.2012.4.411 23138511 · DOI
  17. Boyle J, Yeter D, Aschner M (2021). Estimated IQ points and lifetime earnings lost to early childhood blood lead levels in the United States. Sci Total Environ 778, 146307. doi: 10.1016/j.scitotenv.2021.146307 34030355 · DOI
  18. Butera A, Smirnova L, Ferrando-May E (2023). Deconvoluting gene and environment interactions to develop “epigenetic score meter” of disease. EMBO Mol Med 15, e18208. doi: 10.15252/emmm.202318208 37538003 PMC10493573 · DOI
  19. Caloni F, De Angelis I and Hartung T (2022). Replacement of animal testing by integrated approaches to testing and assessment (IATA): A call for in vivitrosi. Arch Toxicol 96, 1935– 1950. doi: 10.1007/s00204-022-03299-x 35503372 PMC9151502 · DOI
  20. Cediel-Ulloa A, Lupu DL, Johansson Y (2022). Impact of endocrine disrupting chemicals on neurodevelopment: The need for better testing strategies for endocrine disruption-induced developmental neurotoxicity. Expert Rev Endocrinol Metab 17, 131– 141. doi: 10.1080/17446651.2022.2044788 35255767 · DOI
  21. Chesnut M, Hartung T, Hogberg HT (2021a). Human oligodendrocytes and myelin in vitro to evaluate developmental neurotoxicity. Int J Mol Sci 22, 7929. doi: 10.3390/ijms22157929 34360696 PMC8347131 · DOI
  22. Chesnut M, Paschoud H, Repond C (2021b). Human 3D iPSC-derived brain model to study chemical-induced myelin disruption. Int J Mol Sci 22, 9473. doi: 10.3390/ijms22179473 34502381 PMC8430601 · DOI
  23. Coecke S, Goldberg AM, Allen S (2007). Workgroup report: Incorporating in vitro alternative methods for developmental neurotoxicity into international hazard and risk assessment strategies. Environ Health Perspect 115, 924– 931. doi: 10.1289/ehp.9427 17589601 PMC1892131 · DOI
  24. Cohn EF, Clayton BLL, Madhavan M (2024). Pervasive environmental chemicals impair oligodendrocyte development. Nat Neurosci, online ahead of print. doi: 10.1038/s41593-024-01599-2 PMC11088982 38528201 · DOI
  25. Crofton KM, Mundy WR, Lein PJ (2011). Developmental neurotoxicity testing: Recommendations for developing alternative methods for the screening and prioritization of chemicals. ALTEX 28, 9– 15. doi: 10.14573/altex.2011.1.009 21311847 · DOI
  26. Crofton K, Fritsche E, Ylikomi T and Bal-Price A (2014). International STakeholder NETwork (ISTNET) for creating a developmental neurotoxicity testing (DNT) roadmap for regulatory purposes. ALTEX 31, 223– 224. doi: 10.14573/altex.1402121 24794006 · DOI
  27. Crofton KM and Mundy WR (2021). External scientific report on the interpretation of data from the developmental neurotoxicity in vitro testing assays for use in integrated approaches for testing and assessment. EFSA Support Publ 18, 6924E. doi: 10.2903/sp.efsa.2021.en-6924 · DOI
  28. Diemar MG, Vinken M, Teunis M (2024). Report of the First ONTOX stakeholder network meeting: Digging under the surface of ONTOX together with the stakeholders. Altern Lab Anim 52, 117– 131. doi: 10.1177/02611929231225730 38235727 · DOI
  29. Fritsche E, Crofton KM, Hernandez AF (2017). OECD/EFSA workshop on developmental neurotoxicity (DNT): The use of non-animal test methods for regulatory purposes. ALTEX 34, 311– 315. doi: 10.14573/altex.1701171 28407175 · DOI · Paper page
  30. Fritsche E, Barenys M, Klose J (2018). Current availability of stem cell-based in vitro methods for developmental neurotoxicity (DNT) testing. Toxicol Sci 165, 21– 30. doi: 10.1093/toxsci/kfy178 29982830 · DOI
  31. Furxhi I and Murphy F (2020). Predicting in vitro neurotoxicity induced by nanoparticles using machine learning. Int J Mol Sci 21, 5280. doi: 10.3390/ijms21155280 32722414 PMC7432486 · DOI
  32. Gaylord A, Osborne G, Ghassabian A (2020). Trends in neurodevelopmental disability burden due to early life chemical exposure in the USA from 2001 to 2016: A population-based disease burden and cost analysis. Mol Cell Endocrinol 502, 110666. doi: 10.1016/j.mce.2019.110666 31952890 PMC7073246 · DOI
  33. Grandjean P and Landrigan PJ (2006). Developmental neurotoxicity of industrial chemicals. Lancet 368, 2167– 2178. doi: 10.1016/S0140-6736(06)69665-7 17174709 · DOI · Paper page
  34. Grandjean P and Landrigan PJ (2014). Neurobehavioural effects of developmental toxicity. Lancet Neurol 13, 330– 338. doi: 10.1016/S1474-4422(13)70278-3 24556010 PMC4418502 · DOI · Paper page
  35. Groot MWGM, Westerink RHS and Dingemans MML (2013). Don’t judge a neuron only by its cover: Neuronal function in in vitro developmental neurotoxicity testing. Toxicol Sci 132, 1– 7. doi: 10.1093/toxsci/kfs269 22961093 · DOI
  36. Hartung T, van Vliet E, Jaworska J (2012). Systems toxicology. ALTEX 29, 119– 128. doi: 10.14573/altex.2012.2.119 22562485 · DOI
  37. Hartung T, Luechtefeld T, Maertens A (2013a). Integrated testing strategies for safety assessments. ALTEX 30, 3– 18. doi: 10.14573/altex.2013.1.003 23338803 PMC3800026 · DOI
  38. Hartung T and Tsatsakis AM (2021). The state of the scientific revolution in toxicology. ALTEX 38, 379– 386. doi: 10.14573/altex.2106101 34164696 · DOI
  39. Hartung T (2023a). ToxAIcology – The evolving role of artificial intelligence in advancing toxicology and modernizing regulatory science. ALTEX 40, 559– 570. doi: 10.14573/altex.2309191 37889187 · DOI
  40. Hartung T (2023b). A call for a human exposome project. ALTEX 40, 4– 33. doi: 10.14573/altex.2301061 36648285 · DOI
  41. Hartung T, Smirnova L, Morales Pantoja IE (2023). The Baltimore declaration toward the exploration of organoid intelligence. Front Sci 1, 1017235. doi: 10.3389/fsci.2023.1017235 · DOI
  42. Hartung T, Morales Pantoja IE and Smirnova L (2024). Brain organoids and organoid intelligence (OI) from ethical, legal, and social points of view. Front Artif Intell 6, 1307613. doi: 10.3389/frai.2023.1307613 38249793 PMC10796793 · DOI
  43. Hernández-Jerez AF, Adriaanse PI, Aldrich AP (2021). Development of integrated approaches to testing and assessment (IATA) case studies on developmental neurotoxicity (DNT) risk assessment. EFSA J 19, e06599. doi: 10.2903/j.efsa.2021.6599 · DOI
  44. Hertz-Picciotto I and Delwiche L (2009). The rise in autism and the role of age at diagnosis. Epidemiology 20, 84– 90. doi: 10.1097/ede.0b013e3181902d15 19234401 PMC4113600 · DOI · Paper page
  45. Hogberg HT, Kinsner-Ovaskainen A, Coecke S (2010). mRNA expression is a relevant tool to identify developmental neurotoxicants using an in vitro approach. Toxicol Sci 113, 95– 115. doi: 10.1093/toxsci/kfp175 19651682 · DOI
  46. Hogberg HT, Sobanski T, Novellino A (2011). Application of micro-electrode arrays (MEAs) as an emerging technology for developmental neurotoxicity: Evaluation of domoic acid-induced effects in primary cultures of rat cortical neurons. Neurotoxicology 32, 158– 168. doi: 10.1016/j.neuro.2010.10.007 21056592 · DOI
  47. Hogberg HT, Bressler J, Christian KM (2013). Toward a 3D model of human brain development for studying gene/environment interactions. Stem Cell Res Ther 4, S4. doi: 10.1186/scrt365 24564953 PMC4029162 · DOI
  48. Hogberg HT, de Cássia da Silveira e Sá R, Kleensang A (2021). Organophosphorus flame retardants are developmental neurotoxicants in a rat primary BrainSphere in vitro model. Arch Toxicol 95, 207– 228. doi: 10.1007/s00204-020-02903-2 33078273 PMC7811506 · DOI
  49. Hogberg HT and Smirnova L (2022). The future of 3D brain cultures in developmental neurotoxicity testing. Front Toxicol 4, 808620. doi: 10.3389/ftox.2022.808620 35295222 PMC8915853 · DOI
  50. Honegger P, Lenoir D and Favrod P (1979). Growth and differentiation of aggregating fetal brain cells in a serum-free defined medium. Nature 282, 305– 308. doi: 10.1038/282305a0 503203 · DOI
  51. Huang Q, Tang B, Romero JC (2022). Shell microelectrode arrays (MEAs) for brain organoids. Sci Adv 8, eabq5031. doi: 10.1126/sciadv.abq5031 35977026 PMC9385157 · DOI
  52. Ilieva M, Fex Svenningsen Å, Thorsen M (2018). Psychiatry in a dish: Stem cells and brain organoids modeling autism spectrum disorders. Biol Psychiatry 83, 558– 568. doi: 10.1016/j.biopsych.2017.11.011 29295738 · DOI
  53. Juberg DR, Fox DA, Forcelli PA (2023). A perspective on in vitro developmental neurotoxicity test assay results: An expert panel review. Regul Toxicol Pharmacol 143, 105444. doi: 10.1016/j.yrtph.2023.105444 37442267 · DOI
  54. Keown C, Shih P, Nair A (2013). Local functional over-connectivity in posterior brain regions is associated with symptom severity in autism spectrum disorders. Cell Rep 5, 567– 572. doi: 10.1016/j.celrep.2013.10.003 24210815 PMC5708538 · DOI
  55. Kilpatrick S, Irwin C and Singh KK (2023). Human pluripotent stem cell (hPSC) and organoid models of autism: Opportunities and limitations. Transl Psychiatry 13, 217. doi: 10.1038/s41398-023-02510-6 37344450 PMC10284884 · DOI
  56. Kleensang A, Maertens A, Rosenberg M (2014). Pathways of toxicity. ALTEX 31, 53– 61. doi: 10.14573/altex.1309261 24127042 PMC4041485 · DOI
  57. Kleinstreuer N and Hartung T (2024). Artificial intelligence (AI) – It’s the end of the tox as we know it (and I feel fine) – AI for predictive toxicology. Arch Toxicol 98, 735– 754. doi: 10.1007/s00204-023-03666-2 38244040 PMC10861653 · DOI
  58. Knight J, Hartung T and Rovida C (2023). 4.2 million and counting… the animal toll for REACH systemic toxicity studies. ALTEX 40, 389– 407. doi: 10.14573/altex.2303201 37470350 · DOI
  59. Kobolak J, Teglasi A, Bellak T (2020). Human induced pluripotent stem cell-derived 3D-neurospheres are suitable for neurotoxicity screening. Cells 9, 1122. doi: 10.3390/cells9051122 32369990 PMC7290365 · DOI
  60. Krewski D, Andersen M, Tyshenko MG (2020). Toxicity testing in the 21st century: Progress in the past decade and future perspectives. Arch Toxicol 94, 1– 58. doi: 10.1007/s00204-019-02613-4 31848664 · DOI
  61. Krug AK, Kolde R, Gaspar JA (2013a). Human embryonic stem cell-derived test systems for developmental neurotoxicity: A transcriptomics approach. Arch Toxicol 87, 123– 143. doi: 10.1007/s00204-012-0967-3 23179753 PMC3535399 · DOI
  62. Krug AK, Balmer NV, Matt F (2013b). Evaluation of a human neurite growth assay as specific screen for developmental neurotoxicants. Arch Toxicol 87, 2215– 2231. doi: 10.1007/s00204-013-1072-y 23670202 · DOI
  63. Kuehn BM (2010). Increased risk of ADHD associated with early exposure to pesticides, PCBs. JAMA 304, 27– 28. doi: 10.1001/jama.2010.860 20606139 · DOI
  64. La Merrill MA, Vandenberg LN, Smith MT (2020). Consensus on the key characteristics of endocrine-disrupting chemicals as a basis for hazard identification. Nat Rev Endocrinol 16, 45– 57. doi: 10.1038/s41574-019-0273-8 31719706 PMC6902641 · DOI · Paper page
  65. Lancaster M, Renner M, Martin CA (2013). Cerebral organoids model human brain development and microcephaly. Nature 501, 373– 379. doi: 10.1038/nature12517 23995685 PMC3817409 · DOI · Paper page
  66. Lee J and Freeman JL (2014). Zebrafish as a model for developmental neurotoxicity assessment: The application of the zebrafish in defining the effects of arsenic, methylmercury, or lead on early neurodevelopment. Toxics 2, 464– 495. doi: 10.3390/toxics2030464 · DOI
  67. Lein P, Silbergeld E, Locke P (2005). In vitro and other alternative approaches to developmental neurotoxicity testing (DNT). Environ Toxicol Pharmacol 19, 735– 744. doi: 10.1016/j.etap.2004.12.035 21783550 · DOI
  68. Lein P, Locke P and Goldberg A (2007). Meeting report: Alternatives for developmental neurotoxicity testing. Environ Health Perspect 115, 764– 768. doi: 10.1289/ehp.9841 17520065 PMC1867989 · DOI
  69. Leist M, Efremova L and Karreman C (2010). Food for thought … considerations and guidelines for basic test method descriptions in toxicology. ALTEX 27, 309– 317. doi: 10.14573/altex.2010.4.309 21240472 · DOI
  70. Leist M, Hasiwa N, Daneshian M (2012). Validation and quality control of replacement alternatives – Current status and future challenges. Toxicol Res 1, 8– 22. doi: 10.1039/c2tx20011b · DOI · Paper page
  71. Leist M, Hasiwa N, Rovida C (2014). Consensus report on the future of animal-free systemic toxicity testing. ALTEX 31, 341– 356. doi: 10.14573/altex.1406091 25061899 · DOI
  72. Leist M, Ghallab A, Graepel R (2017). Adverse outcome pathways: Opportunities, limitations and open questions. Arch Toxicol 91, 3477– 3505. doi: 10.1007/s00204-017-2045-3 29051992 · DOI · Paper page
  73. Li S and Xia M (2019). Review of high-content screening applications in toxicology. Arch Toxicol 93, 3387– 3396. doi: 10.1007/s00204-019-02593-5 31664499 PMC7011178 · DOI
  74. Luderer U, Eskenazi B, Hauser R (2019). Proposed key characteristics of female reproductive toxicants as an approach for organizing and evaluating mechanistic data in hazard assessment. Environ Health Perspect 127, 075001. doi: 10.1289/ehp4971 31322437 PMC6791466 · DOI
  75. Maass C, Schaller S, Dallmann A (2023). Considering developmental neurotoxicity in vitro data for human health risk assessment using physiologically-based kinetic modeling: Deltamethrin case study. Toxicol Sci 192, 59– 70. doi: 10.1093/toxsci/kfad007 36637193 PMC10025876 · DOI
  76. Makris SL, Raffaele K, Allen S (2009). A retrospective performance assessment of the developmental neurotoxicity study in support of OECD test guideline 426. Environ Health Perspect 117, 17– 25. doi: 10.1289/ehp.11447 19165382 PMC2627860 · DOI
  77. Marx U, Akabane T, Andersson T (2020). Biologyinspired microphysiological systems to advance patient benefit and animal welfare in drug development. ALTEX 37, 365– 394. doi: 10.14573/altex.2001241 32113184 PMC7863570 · DOI
  78. Meigs L, Smirnova L, Rovida C (2018). Animal testing and its alternatives – The most important omics is economics. ALTEX 35, 275– 305. doi: 10.14573/altex.1807041 30008008 · DOI · Paper page
  79. Modafferi S, Zhong X, Kleensang A (2021). Gene-environment interactions in developmental neurotoxicity: A case study of synergy between chlorpyrifos and CHD8 knockout in human BrainSpheres. Environ Health Perspect 129, 77001. doi: 10.1289/ehp8580 34259569 PMC8278985 · DOI
  80. Moore NP, Beekhuijzen M, Boogaard PJ (2016). Guidance on the selection of cohorts for the extended one-generation reproduction toxicity study (OECD test guideline 443). Regul Toxicol Pharmacol 80, 32– 40. doi: 10.1016/j.yrtph.2016.05.036 27245879 · DOI
  81. Morales Pantoja IE, Smirnova L, Muotri AR (2023a). First organoid intelligence (OI) workshop to form an OI community. Front Artif Intell 6, 1116870. doi: 10.3389/frai.2023.1116870 36925616 PMC10013972 · DOI
  82. Morales Pantoja IE, Ding L, Leite PEC (2023b). A novel approach to increase glial cell populations in brain microphysiological systems. Adv Biol, e2300198. Online ahead of print. doi: 10.1002/adbi.202300198 PMC11156795 38062868 · DOI
  83. Mundy WR, Padilla S, Breier JM (2015). Expanding the test set: Chemicals with potential to disrupt mammalian brain development. Neurotoxicol Teratol 52, 25– 35. doi: 10.1016/j.ntt.2015.10.001 26476195 · DOI
  84. Nishimura Y, Murakami S, Ashikawa Y (2015). Zebrafish as a systems toxicology model for developmental neurotoxicity testing. Congenit Anom (Kyoto) 55, 1– 16. doi: 10.1111/cga.12079 25109898 · DOI
  85. NRC – National Research Council (2007). Toxicity Testing in the 21st Century: A Vision and a Strategy. Washington, DC, USA: The National Academies Press.. doi: 10.17226/11970 · DOI
  86. Nyffeler J, Chovancova P, Dolde X (2018). A structure-activity relationship linking non-planar PCBs to functional deficits of neural crest cells: New roles for connexins. Arch Toxicol 92, 1225– 1247. doi: 10.1007/s00204-017-2125-4 29164306 · DOI
  87. OECD (2001). Test No. 416: Two-Generation Reproduction Toxicity. OECD Guidelines for the Testing of Chemicals, Section 4. OECD Publishing, Paris, doi: 10.1787/9789264070868-en · DOI
  88. OECD (2007). Test No. 426: Developmental Neurotoxicity Study. OECD Guidelines for the Testing of Chemicals, Section 4. OECD Publishing, Paris. doi: 10.1787/9789264067394-en · DOI · Paper page
  89. OECD (2018). Test No. 443: Extended One-Generation Reproductive Toxicity Study. OECD Guidelines for the Testing of Chemicals, Section 4. OECD Publishing, Paris. doi: 10.1787/9789264185371-en · DOI
  90. Pamies D, Bal-Price A, Simeonov A (2017). Good cell culture practice for stem cells and stem-cell-derived models. ALTEX 34, 95– 132. doi: 10.14573/altex.1607121 27554434 · DOI · Paper page
  91. Pamies D, Block K, Lau P (2018). Rotenone exerts developmental neurotoxicity in a human brain spheroid model. Toxicol Appl Pharmacol 354, 101– 114. doi: 10.1016/j.taap.2018.02.003 29428530 PMC6082736 · DOI
  92. Persson M and Hornberg JJ (2016). Advances in predictive toxicology for discovery safety through high content screening. Chem Res Toxicol 29, 1998– 2007. doi: 10.1021/acs.chemrestox.6b00248 27766849 · DOI
  93. Pessah IN and Lein PJ (2008). Evidence for environmental susceptibility in autism – What we need to know about gene x environment interactions. In Zimmerman A (ed.), Autism: Current Theories and Evidence (409– 428). Humana Press.
  94. Pistollato F, de Gyves EM, Carpi D (2020). Assessment of developmental neurotoxicity induced by chemical mixtures using an adverse outcome pathway concept. Environ Health 19, 23. doi: 10.1186/s12940-020-00578-x 32093744 PMC7038628 · DOI
  95. Pitzer EM, Shafer TJ and Herr DW (2023). Identification of neurotoxicology (NT)/developmental neurotoxicology (DNT) adverse outcome pathways and key event linkages with in vitro DNT screening assays. Neurotoxicology 99, 184– 194. doi: 10.1016/j.neuro.2023.10.007 37866692 PMC12117389 · DOI
  96. Rempel E, Hoelting L, Waldmann T (2015). A transcriptome-based classifier to identify developmental toxicants by stem cell testing: Design, validation and optimization for histone deacetylase inhibitors. Arch Toxicol 89, 1599– 1618. doi: 10.1007/s00204-015-1573-y 26272509 PMC4551554 · DOI
  97. Rice D and Barone S Jr. (2000). Critical periods of vulnerability for the developing nervous system: Evidence from humans and animal models. Environ Health Perspect 108, Suppl 3, 511– 533. doi: 10.1289/ehp.00108s3511 10852851 PMC1637807 · DOI · Paper page
  98. Rodier PM (1995). Developing brain as a target of toxicity. Environ Health Perspect 103, Suppl 6, 73– 76. doi: 10.1289/ehp.95103s673 PMC1518932 8549496 · DOI
  99. Romero JC, Berlinicke C, Chow S (2023). Oligodendrogenesis and myelination tracing in a CRISPR/Cas9-engineered brain microphysiological system. Front Cell Neurosci 16, 1094291. doi: 10.3389/fncel.2022.1094291 36744062 PMC9893511 · DOI
  100. Rossignol D, Genuis S and Frye R (2014). Environmental toxicants and autism spectrum disorders: A systematic review. Transl Psychiatry 4, e360. doi: 10.1038/tp.2014.4 24518398 PMC3944636 · DOI · Paper page
  101. Rovida C, Alépée N, Api AM (2015). Integrated testing strategies (ITS) for safety assessment. ALTEX 32, 25– 40. doi: 10.14573/altex.1411011 25413849 · DOI
  102. Rovida C, Busquet F, Leist M (2023). REACH outnumbered! The future of REACH and animal numbers. ALTEX 40, 367– 388. doi: 10.14573/altex.2307121 37470349 · DOI
  103. Russo FB, Brito A, de Freitas AM (2019). The use of iPSC technology for modeling autism spectrum disorders. Neurobiol Dis 130, 104483. doi: 10.1016/j.nbd.2019.104483 31129084 · DOI
  104. Sachana M, Bal-Price A, Crofton KM (2019). International regulatory and scientific effort for improved developmental neurotoxicity testing. Toxicol Sci 167, 45– 57. doi: 10.1093/toxsci/kfy211 30476307 · DOI
  105. Sachana M, Shafer TJ and Terron A (2021a). Toward a better testing paradigm for developmental neurotoxicity: OECD efforts and regulatory considerations. Biology 10, 86. doi: 10.3390/biology10020086 33498772 PMC7912397 · DOI · Paper page
  106. Sachana M, Willett C, Pistollato F (2021b). The potential of mechanistic information organised within the AOP framework to increase regulatory uptake of the developmental neurotoxicity (DNT) in vitro battery of assays. Reprod Toxicol 103, 159– 170. doi: 10.1016/j.reprotox.2021.06.006 34147625 PMC8279093 · DOI
  107. Sagiv SK, Thurston SW, Bellinger DC (2010). Prenatal organochlorine exposure and behaviors associated with attention deficit hyperactivity disorder in school-aged children. Am J Epidemiol 171, 593– 601. doi: 10.1093/aje/kwp427 20106937 PMC2842227 · DOI
  108. Santos JLS, Araújo CA, Rocha CAG (2023). Modeling autism spectrum disorders with induced pluripotent stem cell-derived brain organoids. Biomolecules 13, 260. doi: 10.3390/biom13020260 36830629 PMC9953447 · DOI
  109. Schiffelers MWA, Blaauboer BJ, Bakker WE (2015). Regulatory acceptance and use of the extended one generation reproductive toxicity study within Europe. Regul Toxicol Pharmacol 71, 114– 124. doi: 10.1016/j.yrtph.2014.10.012 25445002 · DOI
  110. Schmidt BZ, Lehmann M, Gutbier S (2016). In vitro acute and developmental neurotoxicity screening: An overview of cellular platforms and high-throughput technical possibilities. Arch Toxicol 91, 1– 33. doi: 10.1007/s00204-016-1805-9 27492622 · DOI
  111. Schmuck MR, Temme T, Dach K (2017). Omnisphero: A high-content image analysis (HCA) approach for phenotypic developmental neurotoxicity (DNT) screenings of organoid neurosphere cultures in vitro. Arch Toxicol 91, 2017– 2028. doi: 10.1007/s00204-016-1852-2 27722930 · DOI
  112. Schwartz MP, Hou Z, Propson NE (2015). Human pluripotent stem cell-derived neural constructs for predicting neural toxicity. Proc Natl Acad Sci U S A 112, 12516– 12521. doi: 10.1073/pnas.1516645112 26392547 PMC4603492 · DOI · Paper page
  113. Shafer TJ (2019). Application of microelectrode array approaches to neurotoxicity testing and screening. Adv Neurobiol 22, 275– 297. doi: 10.1007/978-3-030-11135-9_12 31073941 · DOI
  114. Smirnova L, Hogberg HT, Leist M (2014). Developmental neurotoxicity – Challenges in the 21st century and in vitro opportunities. ALTEX 31, 129– 156. doi: 10.14573/altex.1403271 24687333 PMC4778747 · DOI
  115. Smirnova L, Seiler AEM and Luch A (2015a). microRNA profiling as tool for developmental neurotoxicity testing (DNT). Curr Protoc Toxicol 64, 20.9.1– 22. doi: 10.1002/0471140856.tx2009s64 26344224 · DOI
  116. Smirnova L, Harris G, Leist M (2015b). Cellular resilience. ALTEX 32, 247– 260. doi: 10.14573/altex.1509271 26536287 · DOI
  117. Smirnova L, Kleinstreuer N, Corvi R (2018). 3S – Systematic, systemic, and systems biology and toxicology. ALTEX 35, 139– 162. doi: 10.14573/altex.1804051 29677694 PMC6696989 · DOI
  118. Smirnova L, Caffo BS, Gracias DH (2023a). Organoid intelligence (OI): The new frontier in biocomputing and intelligence-in-a-dish. Front Sci 1, 1017235. doi: 10.3389/fsci.2023.1017235 · DOI
  119. Smirnova L, Morales Pantoja IE and Hartung T (2023b). Organoid Intelligence (OI) – The ultimate functionality of a brain microphysiological system. ALTEX 40, 191– 203. doi: 10.14573/altex.2303261 37009773 · DOI
  120. Smirnova L and Hartung T (2024). The promise and potential of brain organoids. Adv Healthc Mater, e2302745. Online ahead of print. doi: 10.1002/adhm.202302745 38252094 · DOI
  121. Spînu N, Cronin MTD, Lao J (2022). Probabilistic modelling of developmental neurotoxicity based on a simplified adverse outcome pathway network. Comput Toxicol 21, 100206. doi: 10.1016/j.comtox.2021.100206 35211661 PMC8857173 · DOI
  122. Suciu I, Pamies D, Peruzzo R (2023a). GxE interactions as a basis for toxicological uncertainty. Arch Toxicol 97, 2035– 2049. doi: 10.1007/s00204-023-03500-9 37258688 PMC10256652 · DOI
  123. Suciu I, Delp J, Gutbier S (2023b). Definition of the neurotoxicity-associated metabolic signature triggered by berberine and other respiratory chain inhibitors. Antioxidants 13, 49. doi: 10.3390/antiox13010049 38247474 PMC10812665 · DOI
  124. van Thriel C, Westerink RH, Beste C (2012). Translating neurobehavioural endpoints of developmental neurotoxicity tests into in vitro assays and readouts. Neurotoxicology 33, 911– 924. doi: 10.1016/j.neuro.2011.10.002 22008243 PMC3288589 · DOI
  125. van Vliet E, Stoppini L, Balestrino M (2007). Electrophysiological recording of re-aggregating brain cell cultures on multi-electrode arrays to detect acute neurotoxic effects. Neurotoxicology 28, 1136– 1146. doi: 10.1016/j.neuro.2007.06.004 17692379 · DOI · Paper page
  126. van Vliet E, Morath S, Linge J (2008). A novel in vitro metabolomics approach for neurotoxicity testing, proof of principle for methyl mercury chloride and caffeine. Neurotoxicology 29, 1– 12. doi: 10.1016/j.neuro.2007.09.007 18023877 · DOI
  127. van Vliet E, Daneshian M, Beilmann M (2014). Current approaches and future role of high content imaging in safety sciences and drug discovery. ALTEX 31, 479– 493. doi: 10.14573/altex.1405271 25027442 · DOI
  128. Villa C, Combi R, Conconi D (2021). Patient-derived induced pluripotent stem cells (iPSCs) and cerebral organoids for drug screening and development in autism spectrum disorder: Opportunities and challenges. Pharmaceutics 13, 280. doi: 10.3390/pharmaceutics13020280 33669772 PMC7922555 · DOI
  129. Vinken M, Benfenati E, Busquet F (2021). Safer chemicals using less animals: Kick-off of the European ONTOX project. Toxicology 458, 152846. doi: 10.1016/j.tox.2021.152846 34216698 · DOI
  130. Wegscheid ML, Anastasaki C, Hartigan KA (2021). Patient-derived iPSC-cerebral organoid modeling of the 17q11.2 microdeletion syndrome establishes CRLF3 as a critical regulator of neurogenesis. Cell Rep 36, 109315. doi: 10.1016/j.celrep.2021.109315 34233200 PMC8278229 · DOI
  131. Willett CE (2018). The use of adverse outcome pathways (AOPs) to support chemical safety decisions within the context of integrated approaches to testing and assessment (IATA). In Kojima H, Seidle T and Spielmann H (eds), Alternatives to Animal Testing (83– 90). Singapore: Springer. doi: 10.1007/978-981-13-2447-5_11 · DOI
  132. Yi Z, Gao H, Ji X (2021). Mapping drug-induced neuropathy through in-situ motor protein tracking and machine learning. J Am Chem Soc 143, 14907– 14915. doi: 10.1021/jacs.1c07312 34469145 · DOI
  133. Zhang L, Li M, Zhang D (2023). Developmental neurotoxicity (DNT) QSAR combination prediction model establishment and structural characteristics interpretation. Toxicol Res 13, tfad116. doi: 10.1093/toxres/tfad116 PMC10762666 38178999 · DOI
  134. Zhong X, Harris G, Smirnova L (2020). Antidepressant paroxetine exerts developmental neurotoxicity in an iPSC-derived 3D human brain model. Front Cell Neurosci 14, 25. doi: 10.3389/fncel.2020.00025 32153365 PMC7047331 · DOI

Venue
ALTEX
Publisher
ALTEX Edition
Published
2024
ISSN
1868-596X
Cited by
12
References
8

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review