Retrospective analysis and decentralized distribution to improve the lifecycle of Ah receptor research assets

Scientific progress benefits from the sharing of "research assets" such as data, reagents, models, and experimental samples. To improve asset shareability, we evaluated the availability, quality, and characterization of recombinant DNA molecules, recombinant mouse models, and tissue samples described by our laboratory in ten publications spanning over thirty years. Employing state-of-the-art molecular technologies, we identified existing samples, updated their localization, generated modern sequences and maps of recombinant models, and ported the associated metadata to an internal blockchain-dependent resource using a standardized description for each asset class. We also created non-fungible tokens representing research assets on the public blockchain network Solana. In addition to providing an audit of previously reported shareable assets and improving the value of recombinant models, this re-analysis also provides evidence for the utility of extant tissue samples that may be difficult and expensive to regenerate. The results demonstrate how retrospective analysis can improve and expand upon the spectrum of shareable research assets through updates on molecular characterization and physical location, as well as improving the availability of biological samples of potential high experimental value. Moreover, the development of a decentralized ledger harboring this revised metadata provides a path to the description and tokenization of scientific assets and provides a strategy to extend the life of scientific assets even after laboratories or sources close.

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Publication Details

Journal
Biochemical Pharmacology
Published
2025-03-19
DOI
https://doi.org/10.1016/j.bcp.2025.116874
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
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article

Retrospective analysis and decentralized distribution to improve the lifecycle of Ah receptor research assets

Christopher Harrison, C. Dustin Rubinstein, Christopher A. Bradfield, Patrick R. Carney et al.
Biochemical Pharmacology
Scientific Computing and Data Management
article

Retrospective analysis and decentralized distribution to improve the lifecycle of Ah receptor research assets

Christopher Harrison, C. Dustin Rubinstein, Christopher A. Bradfield, Patrick R. Carney, Brenda L. Rojas, Alex Veith, Aiqing Wu, Mark E. Berres, Emmanuel Vazquez-Rivera
article en

Abstract

Scientific progress benefits from the sharing of "research assets" such as data, reagents, models, and experimental samples. To improve asset shareability, we evaluated the availability, quality, and characterization of recombinant DNA molecules, recombinant mouse models, and tissue samples described by our laboratory in ten publications spanning over thirty years. Employing state-of-the-art molecular technologies, we identified existing samples, updated their localization, generated modern sequences and maps of recombinant models, and ported the associated metadata to an internal blockchain-dependent resource using a standardized description for each asset class. We also created non-fungible tokens representing research assets on the public blockchain network Solana. In addition to providing an audit of previously reported shareable assets and improving the value of recombinant models, this re-analysis also provides evidence for the utility of extant tissue samples that may be difficult and expensive to regenerate. The results demonstrate how retrospective analysis can improve and expand upon the spectrum of shareable research assets through updates on molecular characterization and physical location, as well as improving the availability of biological samples of potential high experimental value. Moreover, the development of a decentralized ledger harboring this revised metadata provides a path to the description and tokenization of scientific assets and provides a strategy to extend the life of scientific assets even after laboratories or sources close.

Biochemical PharmacologyVol. 236
University of Wisconsin–Madison (US)
Openalex Percentile: Top 94%
Scientific Computing and Data Management
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