Data Mining a Medieval Medical Text Reveals Patterns in Ingredient Choice That Reflect Biological Activity against Infectious Agents

Author:

Connelly Erin1,del Genio Charo I.2,Harrison Freya3

Affiliation:

1. Schoenberg Institute for Manuscript Studies, Philadelphia, Pennsylvania, USA

2. Centre for Fluid and Complex Systems, School of Computing, Electronics and Mathematics, Coventry University, Coventry, United Kingdom

3. School of Life Sciences, University of Warwick, Coventry, United Kingdom

Abstract

We used established methodologies from network science to identify patterns in medicinal ingredient combinations in a key medieval text, the 15th-century Lylye of Medicynes , focusing on recipes for topical treatments for symptoms of microbial infection. We conducted experiments screening the antimicrobial activity of selected ingredients. These experiments revealed interesting examples of ingredients that potentiated or interfered with each other’s activity and that would be useful bases for future, more detailed experiments. Our results highlight (i) the potential to use methodologies from network science to analyze medieval data sets and detect patterns of ingredient combination, (ii) the potential of interdisciplinary collaboration to reveal different aspects of the ethnopharmacology of historical medical texts, and (iii) the potential development of novel therapeutics inspired by premodern remedies in a time of increased need for new antibiotics.

Funder

University of Pennsylvania

University of Warwick

Publisher

American Society for Microbiology

Subject

Virology,Microbiology

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