Schoenberg Institute for Manuscript Studies, Philadelphia, Pennsylvania, USA
Centre for Fluid and Complex Systems, School of Computing, Electronics and Mathematics, Coventry University, Coventry, United Kingdom.
mBio. 2020 Feb 11;11(1):e03136-19. doi: 10.1128/mBio.03136-19.
The pharmacopeia used by physicians and laypeople in medieval Europe has largely been dismissed as placebo or superstition. While we now recognize that some of the used by medieval physicians could have had useful biological properties, research in this area is limited by the labor-intensive process of searching and interpreting historical medical texts. Here, we demonstrate the potential power of turning medieval medical texts into contextualized electronic databases amenable to exploration by the use of an algorithm. We used established methodologies from network science to reveal patterns in ingredient selection and usage in a key text, the 15th-century , focusing on remedies to treat symptoms of microbial infection. In providing a worked example of data-driven textual analysis, we demonstrate the potential of this approach to encourage interdisciplinary collaboration and to shine a new light on the ethnopharmacology of historical medical texts. We used established methodologies from network science to identify patterns in medicinal ingredient combinations in a key medieval text, the 15th-century , 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.
在中世纪欧洲，医生和非专业人士使用的药典在很大程度上被认为是安慰剂或迷信。虽然我们现在认识到，中世纪医生使用的一些药物可能具有有用的生物特性，但由于搜索和解释历史医学文本的过程非常繁琐，该领域的研究受到限制。在这里，我们展示了一种将中世纪医学文本转化为可通过算法探索的上下文化电子数据库的潜力。我们使用网络科学中的既定方法，揭示了在一本关键的 15 世纪著作——《论药剂学》中，药物成分选择和使用的模式，重点是治疗微生物感染症状的疗法。通过提供数据驱动的文本分析实例，我们展示了这种方法的潜力，鼓励跨学科合作，并为历史医学文本的民族药理学提供新的视角。我们使用网络科学中的既定方法，在一本关键的中世纪著作——《论药剂学》中识别药用成分组合的模式，重点是治疗微生物感染症状的局部治疗方法。我们进行了筛选选定成分的抗菌活性的实验。这些实验揭示了有趣的例子，说明成分之间相互增强或干扰彼此的活性，这将是未来更详细实验的有用基础。我们的结果突出了以下几点：（i）使用网络科学方法分析中世纪数据集并检测成分组合模式的潜力；（ii）跨学科合作揭示历史医学文本民族药理学不同方面的潜力；（iii）在对抗生素需求不断增加的时代，从古代疗法中获得灵感，开发新疗法的潜力。
