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A template wizard for the cocreation of machine-readable data-reporting to harmonize the evaluation of (nano)materials

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Abstract

Making research data findable, accessible, interoperable and reusable (FAIR) is typically hampered by a lack of skills in technical aspects of data management by data generators and a lack of resources. We developed a Template Wizard for researchers to easily create templates suitable for consistently capturing data and metadata from their experiments. The templates are easy to use and enable the compilation of machine-readable metadata to accompany data generation and align them to existing community standards and databases, such as eNanoMapper, streamlining the adoption of the FAIR principles. These templates are citable objects and are available as online tools. The Template Wizard is designed to be user friendly and facilitates using and reusing existing templates for new projects or project extensions. The wizard is accompanied by an online template validator, which allows self-evaluation of the template (to ensure mapping to the data schema and machine readability of the captured data) and transformation by an open-source parser into machine-readable formats, compliant with the FAIR principles. The templates are based on extensive collective experience in nanosafety data collection and include over 60 harmonized data entry templates for physicochemical characterization and hazard assessment (cell viability, genotoxicity, environmental organism dose-response tests, omics), as well as exposure and release studies. The templates are generalizable across fields and have already been extended and adapted for microplastics and advanced materials research. The harmonized templates improve the reliability of interlaboratory comparisons, data reuse and meta-analyses and can facilitate the safety evaluation and regulation process for (nano) materials.

Key points

  • The wizard facilitates the capture of experimental metadata and data via community-agreed templates, ensuring that data types generated by different instruments are linked (spectrometers, flow cytometers, microscopes/plate readers, etc.). SOPs and experimental workflows are also hyperlinked to the templates, supporting data harmonization and interoperability.

  • The Template Wizard was evolved with insight and experience gathered over a decade of EU FP7 and H2020 projects addressing nanoscale materials safety.

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Fig. 1: The eNanoMapper data model illustration for representing methods, materials, investigations and assays (endpoints).
Fig. 2: Template wizard.
Fig. 3: AB templates.
Fig. 4: Parsing of an Excel spreadsheet containing data from a CFE assay.
Fig. 5: Template validator screenshots.
Fig. 6: A schematic representation of the steps required for generation (cocreation) of a new endpoint or assay template using the template wizard.
Fig. 7: List of parameters under the ‘sample information’ section.
Fig. 8: Representative example of a NSDRA reusability assessment report of a project description page.

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Data availability

All material characterization and safety data gathered through the community developed templates during multiple projects are available at the community-recognized repository NanoSafety Data Interface at https://search.data.enanomapper.net/. The following list shows datasets with public licenses and their Zenodo URLs: FP7 NANoREG data (https://search.data.enanomapper.net/projects/nanoreg/; https://zenodo.org/record/3467016), H2020 NanoReg2 data (https://search.data.enanomapper.net/projects/nanoreg2/; https://zenodo.org/record/4713745), H2020 caLIBRAte data (https://search.data.enanomapper.net/projects/calibrate/; https://zenodo.org/record/7193516), H2020 GRACIOUS data (https://search.data.enanomapper.net/projects/gracious/; https://zenodo.org/record/7777590) and H2020 RiskGONE (embargoed until 1 September 2024) (https://search.data.enanomapper.net/projects/riskgone; https://zenodo.org/deposit/8269168). The Zenodo archives are SQL dumps of eNanoMapper database, which could be launched at user machines using the AMBIT docker quick start instructions at https://github.com/ideaconsult/ambit-docker.

Code availability

Open-source packages used in implementation of Nanosafety Data Interface, including the template wizard, are listed below. these are not needed for end-users, who only need a web browser to access the template wizard at NanoSafety Data Interface. Open source NMDataParser (https://github.com/enanomapper/nmdataparser). NMDataParser is a Java library, implementing a configurable parser allowing to convert spreadsheet templates into the internal AMBIT data model, using a JSON file for mapping the objects. The data model can be used for importing into databases, or serialized in different format (W3C RDF, JSON, HDF5). Open source AMBIT software (https://ambit.sourceforge.net/). AMBIT provides chemoinformatics functionality and chemical substance data management (including chemical structures, NMs, unknown or variable composition, complex reaction products or of biological materials and multicomponent chemical substances), all available via REST web services. The eNanoMapper database is compilation of AMBIT software with a specific profile. The REST API also includes the eNanoMapper FAIRification workflow which is used by the template validator. AMBIT/eNanoMapper database Docker distribution (https://github.com/ideaconsult/ambit-docker). Open source Javascript library (https://github.com/ideaconsult/jToxKit) is a client and user interface for the eNanoMapper/AMBIT REST API. Open source (https://github.com/ideaconsult/xlsx-datafill) Javascript library provides template-based data population for Excel XLSX spreadsheets.

References

  1. Hofseth, L. J. Getting rigorous with scientific rigor. Carcinogenesis 39, 21–25 (2018).

    Article  CAS  PubMed  Google Scholar 

  2. Prager, E. M. et al. Improving transparency and scientific rigor in academic publishing. Brain Behav. 9, e01141 (2019).

    Article  PubMed  Google Scholar 

  3. Musen, M. A. et al. Modeling community standards for metadata as templates makes data FAIR. Sci. Data 9, 696 https://doi.org/10.1038/s41597-022-01815-3 (2022).

  4. Hernandez-Boussard, T., Bozkurt, S., Ioannidis, J. P. A. & Shah, N. H. MINIMAR (MINimum Information for Medical AI Reporting): developing reporting standards for artificial intelligence in health care. J. Am. Med. Inf. Assoc. 27, 2011–2015 (2020).

    Article  Google Scholar 

  5. Papadiamantis, A. G. et al. Metadata stewardship in nanosafety research: community-driven organisation of metadata schemas to support fair nanoscience data. Nanomaterials 10, 1–49 (2020).

    Article  Google Scholar 

  6. Percie du Sert, N. et al. Reporting animal research: explanation and elaboration for the ARRIVE guidelines 2.0. PLoS Biol. 18, e3000411 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Moller, P. et al. Minimum Information for Reporting on the Comet Assay (MIRCA): recommendations for describing comet assay procedures and results. Nat. Protoc. 15, 3817–3826 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Faria, M. et al. Minimum information reporting in bio-nano experimental literature. Nat. Nanotechnol. 13, 777–785 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Chetwynd, A. J., Wheeler, K. E. & Lynch, I. Best practice in reporting corona studies: Minimum information about Nanomaterial Biocorona Experiments (MINBE). Nano Today 28, 100758 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Erickson, B. E. Nanomaterial characterization. Chem. Eng. N. Arch. 86, 25–26 (2008).

    Article  Google Scholar 

  11. Drobne, D. Adding toxicological context to nanotoxicity study reporting using the NanoTox metadata list. Small 17, 2005622 (2021).

    Article  CAS  Google Scholar 

  12. Elberskirch, L. et al. Digital research data: from analysis of existing standards to a scientific foundation for a modular metadata schema in nanosafety. Part. Fibre Toxicol. 19, 1 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Ramaswamy, V. & Ozcan, K. What is co-creation? An interactional creation framework and its implications for value creation. J. Bus. Res. 84, 196–205 (2018).

    Article  Google Scholar 

  14. Grönroos, C. & Voima, P. Critical service logic: making sense of value creation and co-creation. J. Acad. Mark. Sci. 41, 133–150 (2013).

    Article  Google Scholar 

  15. Sansone, S.-A. et al. Toward interoperable bioscience data. Nat. Genet. 44, 121–126 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Sansone, S.-A., Rocca-Serra, P., Gonzalez-Beltran, Alejandra Johnson, D. & ISA community. ISA model and serialization specifications 1.0. Zenodo https://doi.org/10.5281/zenodo.163640 (2016).

  17. Thomas, D. G. et al. ISA–TAB–Nano: a specification for sharing nanomaterial research data in spreadsheet-based format. BMC Biotechnol. 13, 2 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Kochev, N. et al. Your spreadsheets can be FAIR: a tool and FAIRification workflow for the eNanoMapper database. Nanomaterials 10, 1908 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Jeliazkova, N. et al. Towards FAIR nanosafety data. Nat. Nanotechnol. 16, 644–654 (2021).

    Article  CAS  PubMed  Google Scholar 

  20. Totaro, S., Crutzen, H. & Riego-Sintes, J. Data logging templates for the environmental, health and safety assessment of nanomaterials. European Commission https://publications.jrc.ec.europa.eu/repository/handle/JRC103178 (2017).

  21. Gottardo, S. et al. GRACIOUS data logging templates for the environmental, health and safety assessment of nanomaterials. European Commission https://publications.jrc.ec.europa.eu/repository/handle/JRC117733 (2019).

  22. Tanoli, Z. et al. Minimal information for chemosensitivity assays (MICHA): a next-generation pipeline to enable the FAIRification of drug screening experiments. Brief. Bioinform. 23, bbab350 (2022).

    Article  PubMed  Google Scholar 

  23. Heller, S. R., McNaught, A., Pletnev, I., Stein, S. & Tchekhovskoi, D. InChI, the IUPAC international chemical identifier. J. Cheminform. 7, 23 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Scheffler, M. et al. FAIR data enabling new horizons for materials research. Nature 604, 635–642 (2022).

    Article  CAS  PubMed  Google Scholar 

  25. Wilkinson, M. D. et al. The FAIR guiding principles for scientific data management and stewardship. Sci. Data 3, 160018 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Jeliazkova, N., Kochev, N. & Tancheva, G. in Data Integrity and Data Governance https://doi.org/10.5992/intechopen.1000857 (2023).

  27. van Rijn, J. et al. European Registry of Materials: global, unique identifiers for (undisclosed) nanomaterials. J. Cheminform. 14, 57 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Lynch, I. et al. Can an InChI for nano address the need for a simplified representation of complex nanomaterials across experimental and nanoinformatics studies? Nanomaterials 10, 2493 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Ammar, A., Evelo, C. & Willighagen, E. FAIR assessment of nanosafety data reusability with community standards. Prepr. ChemRxiv https://doi.org/10.26434/chemrxiv-2022-l8vk8-v2 (2022).

    Article  Google Scholar 

  30. Berrios, D. C., Beheshti, A. & Costes, S. V. FAIRness and usability for open-access omics data systems. Annu. Symp. Proc. AMIA Symp. 2018, 232–241 (2018).

    PubMed  Google Scholar 

  31. Rasmussen, K., Rauscher, H., Kearns, P., González, M. & Riego Sintes, J. Developing OECD test guidelines for regulatory testing of nanomaterials to ensure mutual acceptance of test data. Regul. Toxicol. Pharmacol. 104, 74–83 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Xiarchos, I., Morozinis, A. K., Kavouras, P. & Charitidis, C. A. Nanocharacterization, materials modeling, and research integrity as enablers of sound risk assessment: designing responsible nanotechnology. Small 16, 2001590 (2020).

    Article  CAS  Google Scholar 

  33. Steinhäuser, K. G. & Sayre, P. G. Reliability of methods and data for regulatory assessment of nanomaterial risks. NanoImpact 7, 66–74 (2017).

    Article  Google Scholar 

  34. Hendren, C. O., Lowry, G. V., Unrine, J. M. & Wiesner, M. R. A functional assay-based strategy for nanomaterial risk forecasting. Sci. Total Environ. 536, 1029–1037 (2015).

    Article  CAS  PubMed  Google Scholar 

  35. Gao, X. & Lowry, G. V. Progress towards standardized and validated characterizations for measuring physicochemical properties of manufactured nanomaterials relevant to nano health and safety risks. NanoImpact 9, 14–30 (2018).

    Article  CAS  Google Scholar 

  36. Geitner, N. K. et al. Harmonizing across environmental nanomaterial testing media for increased comparability of nanomaterial datasets. Environ. Sci. Nano 7, 13–36 (2020).

    Article  CAS  Google Scholar 

  37. Modena, M. M., Rühle, B., Burg, T. P. & Wuttke, S. Nanoparticle characterization: what to measure? Adv. Mater. 31, 1901556 (2019).

    Article  Google Scholar 

  38. Rasmussen, K. et al. Physico-chemical properties of manufactured nanomaterials - Characterisation and relevant methods. An outlook based on the OECD testing programme. Regul. Toxicol. Pharmacol. 92, 8–28 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Jeliazkova, N. Data entry template for material composition—part of eNanoMapper Template Wizard. Zenodo https://doi.org/10.5281/zenodo.7751340 (2023).

  40. Preliminary review of OECD test guidelines for their applicability to manufactured nanomaterials. ENV/JM/MONO(2009)21 OECD https://one.oecd.org/document/ENV/JM/MONO(2009)21/en/pdf (2009).

  41. Guidance on sample preparation and dosimetry for the safety testing of manufactured nanomaterials. ENV/JM/MONO(2012)40 OECD https://one.oecd.org/document/ENV/JM/MONO(2012)40/en/pdf (2012).

  42. Report of the OECD expert meeting on the physical chemical properties of manufactured nanomaterials and test guidelines. ENV/JM/MONO(2014)15 vol. 41 OECD https://one.oecd.org/document/ENV/JM/MONO(2014)15/en/pdf (2014).

  43. Physical–chemical parameters: measurements and methods relevant for the regulation of nanomaterials. ENV/JM/MONO(2016)2 vol. 63 OECD https://one.oecd.org/document/ENV/JM/MONO(2016)63/en/pdf (2016).

  44. Guiding principles for measurements and reporting for nanomaterials: physical chemical parameters. ENV/JM/MONO(2019)13 vol. 91 OECD https://one.oecd.org/document/env/jm/mono(2019)13/en/pdf (2019).

  45. Ag Seleci, D. et al. Determining nanoform similarity via assessment of surface reactivity by abiotic and in vitro assays. NanoImpact 26, 100390 (2022).

    Article  CAS  PubMed  Google Scholar 

  46. Koltermann-Jülly, J. et al. Abiotic dissolution rates of 24 (nano)forms of 6 substances compared to macrophage-assisted dissolution and in vivo pulmonary clearance: grouping by biodissolution and transformation. NanoImpact 12, 29–41 (2018).

    Article  Google Scholar 

  47. Keller, J. G. et al. Predicting dissolution and transformation of inhaled nanoparticles in the lung using abiotic flow cells: the case of barium sulfate. Sci. Rep. 10, 458 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Keller, J. G. et al. Variation in dissolution behavior among different nanoforms and its implication for grouping approaches in inhalation toxicity. NanoImpact 23, 100341 (2021).

    Article  CAS  PubMed  Google Scholar 

  49. Li, Y., Fujita, M. & Boraschi, D. Endotoxin contamination in nanomaterials leads to the misinterpretation of immunosafety results. Front. Immunol. 8, 472 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Longhin, E., Moschini, E., El Yamani, N. & Sanchez, M. Consolidated pre-validated guidance document on the determination of ENMs endotoxins content. Deliverable 4.4. RiskGONE https://riskgone.wp.nilu.no/wp-content/uploads/sites/11/2022/02/RiskGONE-D4.4.pdf (2021).

  51. Longhin, E. M., El Yamani, N., Rundén-Pran, E. & Dusinska, M. The alamar blue assay in the context of safety testing of nanomaterials. Front. Toxicol. 4, 981701 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  52. O’Brien, J., Wilson, I., Orton, T. & Pognan, F. Investigation of the alamar blue (resazurin) fluorescent dye for the assessment of mammalian cell cytotoxicity. Eur. J. Biochem. 267, 5421–5426 (2000).

    Article  PubMed  Google Scholar 

  53. Guidance Document on Good In Vitro Method Practices (GIVIMP). OECD https://doi.org/10.1787/9789264304796-en (2018).

  54. Ponti, J. et al. Interlaboratory comparison study of the colony forming efficiency assay for assessing cytotoxicity of nanomaterials. Jt. Res. Cent. https://doi.org/10.2788/406937 (2014).

  55. Rundén-Pran, E. et al. The colony forming efficiency assay for toxicity testing of nanomaterials—modifications for higher throughput. Front. Toxicol. 4, 983316 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Cowie, H. et al. Suitability of human and mammalian cells of different origin for the assessment of genotoxicity of metal and polymeric engineered nanoparticles. Nanotoxicology 9, 57–65 (2015).

    Article  CAS  PubMed  Google Scholar 

  57. Vodenkova, S. et al. An optimized comet-based in vitro DNA repair assay to assess base and nucleotide excision repair activity. Nat. Protoc. 15, 3844–3878 (2020).

    Article  CAS  PubMed  Google Scholar 

  58. Guidance on the safety assessment of nanomaterials in cosmetics. Scientific Committee on Consumer Safety https://health.ec.europa.eu/system/files/2020-10/sccs_o_233_0.pdf (2020).

  59. More, S. et al. Guidance on risk assessment of nanomaterials to be applied in the food and feed chain: human and animal health. EFSA J. 19, e06768 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. More, S. et al. Guidance on technical requirements for regulated food and feed product applications to establish the presence of small particles including nanoparticles. EFSA J. 19, e06769 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. El Yamani, N. et al. The miniaturized enzyme-modified comet assay for genotoxicity testing of nanomaterials. Front. Toxicol. 4, 986318 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Magdolenova, Z., Lorenzo, Y., Collins, A. & Dusinska, M. Can standard genotoxicity tests be applied to nanoparticles? J. Toxicol. Environ. Heal. Part A 75, 800–806 (2012).

    Article  CAS  Google Scholar 

  63. Rajapakse, K., Drobne, D., Kastelec, D. & Marinsek-Logar, R. Experimental evidence of false-positive Comet test results due to TiO 2 particle—assay interactions. Nanotoxicology 7, 1043–1051 (2013).

    Article  CAS  PubMed  Google Scholar 

  64. Bossa, C. et al. FAIRification of nanosafety data to improve applicability of (Q)SAR approaches: a case study on in vitro comet assay genotoxicity data. Comput. Toxicol. 20, 100190 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. El Yamani, N. et al. Hazard identification of nanomaterials: in silico unraveling of descriptors for cytotoxicity and genotoxicity. Nano Today 46, 101581 (2022).

    Article  CAS  Google Scholar 

  66. Collins, A. et al. Measuring DNA modifications with the comet assay: a compendium of protocols. Nat. Protoc. 18, 929–989 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. El Yamani, N. et al. In vitro genotoxicity testing of four reference metal nanomaterials, titanium dioxide, zinc oxide, cerium oxide and silver: towards reliable hazard assessment. Mutagenesis 32, 117–126 (2017).

    Article  CAS  PubMed  Google Scholar 

  68. El Yamani, N. et al. Lack of mutagenicity of TiO2 nanoparticles in vitro despite cellular and nuclear uptake. Mutat. Res. Toxicol. Environ. Mutagen. 882, 503545 (2022).

    Article  CAS  Google Scholar 

  69. Template for mammalian erythrocyte micronucleus test. FDA https://www.fda.gov/food/ingredients-additives-gras-packaging-guidance-documents-regulatory-information/template-mammalian-erythrocyte-micronucleus-test (2004).

  70. Llewellyn, S. V. et al. Assessing the transferability and reproducibility of 3D in vitro liver models from primary human multi-cellular microtissues to cell-line based HepG2 spheroids. Toxicol. Vitr. 85, 105473 (2022).

    Article  CAS  Google Scholar 

  71. Test no. 487: in vitro mammalian cell micronucleus test. OECD https://doi.org/10.1787/9789264264861-en (2016).

  72. Study report and preliminary guidance on the adaptation of the in vitro micronucleus assay (OECD TG 487) for testing of manufactured nanomaterials ENV/CBC/MONO(2022)15. series on testing and assessment vol. 359. OECD https://www.oecd.org/chemicalsafety/testing/series-testing-assessment-publications-number.htm.

  73. Test no. 476: in vitro mammalian cell gene mutation tests using the Hprt and xprt genes. OECD https://www.oecd-ilibrary.org/environment/test-no-476-in-vitro-mammalian-cell-gene-mutation-tests-using-the-hprt-and-xprt-genes_9789264264809-en, https://doi.org/10.1787/20745788 (2016).

  74. Doak, S. H. et al. Mechanistic influences for mutation induction curves after exposure to DNA-reactive carcinogens. Cancer Res. 67, 3904–3911 (2007).

    Article  CAS  PubMed  Google Scholar 

  75. Johnson, G. E. et al. Non-linear dose–response of DNA-reactive genotoxins: recommendations for data analysis. Mutat. Res. Toxicol. Environ. Mutagen. 678, 95–100 (2009).

    Article  CAS  Google Scholar 

  76. Guadagnini, R. et al. Toxicity screenings of nanomaterials: challenges due to interference with assay processes and components of classic in vitro tests. Nanotoxicology 9, 13–24 (2015).

    Article  CAS  PubMed  Google Scholar 

  77. Kroll, A., Pillukat, M. H., Hahn, D. & Schnekenburger, J. Interference of engineered nanoparticles with in vitro toxicity assays. Arch. Toxicol. 86, 1123–1136 (2012).

    Article  CAS  PubMed  Google Scholar 

  78. Collins, A. R. et al. High-throughput toxicity screening and intracellular detection of nanomaterials. Wiley Interdiscip. Rev. Nanomed. Nanobiotechnol. https://doi.org/10.1002/wnan.1413 (2017).

    Article  PubMed  Google Scholar 

  79. Ostermann, M. et al. Label-free impedance flow cytometry for nanotoxicity screening. Sci. Rep. 10, 142 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Jemec, A., Mesarič, T., Sopotnik, M., Sepčić, K. & Drobne, D. in Nanomaterial Characterization 253–268 (John Wiley & Sons, 2016).

  81. Taylor, C. F. et al. Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat. Biotechnol. 26, 889–896 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Sakurai, K., Kurtz, A., Stacey, G., Sheldon, M. & Fujibuchi, W. First proposal of minimum information about a cellular assay for regenerative medicine. Stem Cells Transl. Med. 5, 1345–1361 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  83. Karatzas, P. et al. Development of deep learning models for predicting the effects of exposure to engineered nanomaterials on Daphnia magna. Small 16, 2001080 (2020).

    Article  CAS  Google Scholar 

  84. Test no. 202: Daphnia sp. acute immobilisation test. OECD https://doi.org/10.1787/9789264069947-en (2004).

  85. Test no. 211: Daphnia magna Reproduction Test. OECD https://doi.org/10.1787/9789264185203-en (2012).

  86. Fernández-Cruz, M. L. et al. Quality evaluation of human and environmental toxicity studies performed with nanomaterials—the GUIDEnano approach. Environ. Sci. Nano https://doi.org/10.1039/C7EN00716G (2018).

    Article  Google Scholar 

  87. Klimisch, H. J., Andreae, M. & Tillmann, U. A systematic approach for evaluating the quality of experimental toxicological and ecotoxicological data. Regul. Toxicol. Pharmacol. 25, 1–5 (1997).

    Article  CAS  PubMed  Google Scholar 

  88. Exposure Scenario Library. IOM http://guidenano.iom-world.co.uk/.

  89. Rashid, S. et al. GRACIOUS release and exposure templates. Zenodo https://doi.org/10.5281/zenodo.4665253 (2021).

  90. Sanchez Jimenez, A. et al. Harmonization of release and exposure data collection for nanomaterials. Prep.

  91. Perez-Riverol, Y. et al. The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences. Nucleic Acids Res. 50, D543–D552 (2022).

    Article  CAS  PubMed  Google Scholar 

  92. Additives, E. P. on F. et al. Safety assessment of titanium dioxide (E171) as a food additive. EFSA J. 19, e06585 (2021).

  93. Canada, H. State of the science of titanium dioxide (TiO2) as a food additive. LJMU https://publications.gc.ca/collections/collection_2022/sc-hc/H164-341-2022-eng.pdf (2022).

  94. Corcho, O., Eriksson, M. & Kurowski, K. EOSC interoperability framework: report from the EOSC Executive Board Working Groups FAIR and Architecture. https://doi.org/10.2777/620649 (2021).

  95. The New European Interoperability Framework. European Commission https://ec.europa.eu/isa2/eif_en/.

  96. Basei, G., Rauscher, H., Jeliazkova, N. & Hristozov, D. A methodology for the automatic evaluation of data quality and completeness of nanomaterials for risk assessment purposes. Nanotoxicology 16, 195–216 (2022).

    Article  PubMed  Google Scholar 

  97. Ellis, L. A. et al. Multigenerational exposures of Daphnia magna to pristine and aged silver nanoparticles: epigenetic changes and phenotypical ageing related effects. Small 16, 2000301 (2020).

    Article  CAS  Google Scholar 

  98. Ellis, L.-J. A. et al. Multigenerational exposure to Nano-TiO2 induces ageing as a stress response mitigated by environmental interactions. Adv. NanoBiomed Res. 1, 2000083 (2021).

    Article  CAS  Google Scholar 

  99. Pem, B. et al. Biocompatibility assessment of up-and down-converting nanoparticles: implications of interferences with in vitro assays. Methods Appl. Fluoresc. 7, 014001 (2018).

    Article  PubMed  Google Scholar 

  100. Vinković Vrček, I. et al. Does surface coating of metallic nanoparticles modulate their interference with in vitro assays? RSC Adv. 5, 70787–70807 (2015).

    Article  Google Scholar 

Download references

Acknowledgements

Supported by H2020 projects RiskGONE (no. 814425), HARMLESS (no. 953183), Gov4Nano (no. 814401), SABYDOMA (862296), SBD4NANO (862195), PLASTICFATE (no. 965367), POLYRISK (964766), NANOREG2 (no. 646221), PROPLANET (no. 101091842), NanoSolveIT (no. 814572), CompSafeNano (no. 101008099), TWINALT (no. 952404), VISION (no. 857381), KAPPA project EYFORTX2 (no. T001000099-PZ-2021), TEPCAN project (NCBR no. NOR/POLNOR/TEPCAN/0057/ 2019-00), hCOMET project (COST Action, CA 15132), Slovenian Research Agency projects P1-0207 and P1-0184, and by the Norwegian Research Council project NanoBioReal (no. 288768).

Author information

Authors and Affiliations

  1. Ideaconsult Ltd., Sofia, Bulgaria

    Nina Jeliazkova, Nikolay Kochev, Luchesar Iliev & Vedrin Jeliazkov

  2. Health Effects Laboratory, Department of Environmental Chemistry & Health Effects, The Climate and Environmental Research Institute NILU, Kjeller, Norway

    Eleonora Longhin, Naouale El Yamani, Elise Rundén-Pran & Maria Dusinska

  3. Environmental Health group, Department of Environmental Research and Innovation, Luxembourg Institute of Science and Technology, Belvaux, Luxembourg

    Elisa Moschini & Tommaso Serchi

  4. Institute for Medical Research and Occupational Health, Zagreb, Croatia

    Ivana Vinković Vrček

  5. In Vitro Toxicology Group, Faculty of Medicine, Health and Life Sciences, Institute of Life Sciences, Swansea University Medical School, Singleton Park, Swansea, Wales, UK

    Michael J. Burgum & Shareen H. Doak

  6. Department of Clinical Dentistry, University of Bergen, Bergen, Norway

    Mihaela Roxana Cimpan & Ivan Rios-Mondragon

  7. Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway

    Emil Cimpan

  8. Environment and Health Department, Istituto Superiore di Sanità, Rome, Italy

    Chiara L. Battistelli & Cecilia Bossa

  9. Medical and Biological Research Laboratory, Roumen Tsanev Institute of Molecular Biology–Bulgarian Academy of Sciences, Sofia, Bulgaria

    Rositsa Tsekovska & Margarita D Apostolova

  10. Department of Biology, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia

    Damjana Drobne, Sara Novak & Neža Repar

  11. Department of Bioinformatics–BiGCaT, NUTRIM, Maastricht University, Maastricht, the Netherlands

    Ammar Ammar & Egon Willighagen

  12. Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden

    Penny Nymark

  13. BASF SE, Material Physics, Carl Bosch straße, Ludwigshafen, Germany

    Veronica Di Battista

  14. Department of Environmental and Resource Engineering, DTU, Kgs. Lyngby, Denmark

    Veronica Di Battista

  15. QSAR Lab Ltd., Gdańsk, Poland

    Anita Sosnowska & Tomasz Puzyn

  16. University of Gdańsk, Faculty of Chemistry, Gdansk, Poland

    Anita Sosnowska & Tomasz Puzyn

  17. Department of Analytical Chemistry and Computer Chemistry, Faculty of Chemistry, University of Plovdiv, Plovdiv, Bulgaria

    Nikolay Kochev

  18. School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK

    Katie Reilly & Iseult Lynch

  19. National Institute for Public Health and the Environment, Bilthoven, the Netherlands

    Martine Bakker

  20. LEITAT Technological Centre, Barcelona, Spain

    Camila Delpivo

  21. Spanish National Institute of Health and Safety, Centro Nacional de Verificación de Maquinaria, Barakaldo, Spain

    Araceli Sánchez Jiménez

  22. National Research Centre for the Working Environment, Copenhagen, Denmark

    Ana Sofia Fonseca

  23. Ecotoxicology of Substances and Environmental Matrices Unit, French National Institute for Industrial Environment and Risks, Verneuil-en-Halatte, France

    Nicolas Manier

  24. Department of Environment and Agronomy, National Institute for Agriculture and Food Research and Technology, Spanish National Research Council, Madrid, Spain

    María Luisa Fernandez-Cruz

  25. Institute of Occupational Medicine, Research Avenue North, Edinburgh, UK

    Shahzad Rashid

Authors
  1. Nina Jeliazkova
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  2. Eleonora Longhin
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  3. Naouale El Yamani
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  4. Elise Rundén-Pran
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  5. Elisa Moschini
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  6. Tommaso Serchi
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  7. Ivana Vinković Vrček
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  8. Michael J. Burgum
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  9. Shareen H. Doak
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  10. Mihaela Roxana Cimpan
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  11. Ivan Rios-Mondragon
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  12. Emil Cimpan
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  13. Chiara L. Battistelli
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  14. Cecilia Bossa
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  15. Rositsa Tsekovska
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  16. Damjana Drobne
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  17. Sara Novak
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  18. Neža Repar
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  19. Ammar Ammar
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  20. Penny Nymark
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  21. Veronica Di Battista
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  22. Anita Sosnowska
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  23. Tomasz Puzyn
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  24. Nikolay Kochev
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  25. Luchesar Iliev
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  26. Vedrin Jeliazkov
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  27. Katie Reilly
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  28. Iseult Lynch
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  29. Martine Bakker
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  30. Camila Delpivo
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  31. Araceli Sánchez Jiménez
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  32. Ana Sofia Fonseca
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  33. Nicolas Manier
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  34. María Luisa Fernandez-Cruz
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  35. Shahzad Rashid
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  36. Egon Willighagen
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  37. Margarita D Apostolova
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  38. Maria Dusinska
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Contributions

N.J., N.K., L.I. and V.J. contributed to manuscript conceptualization and draft, nmdataparser software development, template wizard development, template cocreation, and eNanoMapper database creation and management. E.L., N.E.Y., E.R.-P. and M.D. contributed to design templates for cytotoxicity (AB, CFE), genotoxicity (CA, HPRT mutation) and endotoxin determination; paper conceptualization and structure, contribution to the manuscript draft, editing and proofreading. E.M. and T.S. contributed to the adaptation of data collection templates for physicochemical data collection and to the section dedicated to the description of physicochemical information. I.V.V. contributed to template building and data interpretation for physicochemical characterization of NMs and CFE assay, and to the manuscript draft and its proofreading. M.J.B. and S.H.D. contributed the HPRT (Swansea layout) and micronucleus template designs, data interpretation for HPRT and micronucleus assays, and proofreading the draft manuscript. M.R.C. and I.R.-M. contributed to the design of the templates and data interpretation for the bioimpedance assay, and to the manuscript draft. E.C. contributed to the design of the templates and data interpretation for the bioimpedance assay, and to the manuscript draft. C.L.B. and C.B. contributed to the design of the template and data interpretation for the in vitro comet assay, to the anticipated results for template reuse section, and to the manuscript draft. R.T. and M.D.A. contributed to the design of the template and data interpretation of micronucleus assay. M.D.A. prepared the “Instruction for use of templates” and contributed to the manuscript draft, editing and proofreading. D.D. contributed to conceptualization, protocol elaboration, literature review and writing sections of the manuscript. S.N. contributed to literature review and writing sections of the manuscript. N.R. contributed to protocol elaboration. A.A. contributed to integrating Ambit with the NSDRA framework for completeness and reusability assessment, wrote the relevant parts to the integration in the manuscript and created Zenodo records for two templates (FRAS and dynamic dissolution). E.W. contributed to manuscript draft editing and proofreading. P.N. contributed to template design and development for omics metadata and manuscript review and editing. V.D.B. contributed to template building and manuscript draft for dynamic dissolution and FRAS assays. A.S. and T.P. contributed to data quality and analysis and to the manuscript draft. K.R. and I.L. contributed to template building for Daphnia culturing, acute and chronic assays, drafted the section on Daphnia templates and contributed to overall manuscript drafting and revision. M.B. contributed to template building for Gov4Nano templates. C.D., A.S.J. and A.S.F. contributed to data review, analyses, templates building and manuscript draft for ‘ORE template’ and ‘ECR template’. N.M. contributed to data review, analyses, templates building and manuscript draft for acute, chronic and bioaccumulation tests on aquatic organisms. M.L.F.-C. contributed to data review, analyses, templates building and manuscript draft for acute and bioaccumulation tests on aquatic organisms. S.R. contributed to template design and input into the manuscript draft.

Corresponding author

Correspondence to Maria Dusinska.

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Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Protocols thanks Vicki Stone and the other, anonymous, reviewer(s) for their contribution to the peer review process of this work

Additional information

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Related links

Key reference using this protocol

Jeliazkova, N. et al. Nat. Nanotechnol. 16, 644–654 (2021): https://doi.org/10.1038/s41565-021-00911-6

Kochev, N. et al. Nanomaterials 10, 1908 (2020): https://doi.org/10.3390/nano10101908

Key data used in this protocol

Collins, A. et al. Nat. Protoc. 18, 929–989 (2023): https://doi.org/10.1038/s41596-022-00754-y

Longhin, E. M. et al. Front. Toxicol. 4, 981701 (2022): https://doi.org/10.3389/ftox.2022.981701

Ostermann, M. et al. Sci. Rep. 10, 142 (2020): https://doi.org/10.1038/s41598-019-56705-3

Supplementary information

Supplementary Information

Supplementary Methods, Figs. 1–10 and instructions for the use of templates available in the Nanosafety Data Interface.

Supplementary Data 1

Data entry templates.

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Jeliazkova, N., Longhin, E., El Yamani, N. et al. A template wizard for the cocreation of machine-readable data-reporting to harmonize the evaluation of (nano)materials. Nat Protoc (2024). https://doi.org/10.1038/s41596-024-00993-1

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