月经
可穿戴计算机
医学
疾病
内科学
产科
计算机科学
嵌入式系统
作者
Lucas Dosnon,Thomas Rduch,Charlotte Meyer,Inge K. Herrmann
出处
期刊:Cold Spring Harbor Laboratory - medRxiv
日期:2024-03-24
被引量:1
标识
DOI:10.1101/2024.03.22.24304704
摘要
ABSTRACT The pain-free regular monitoring of blood-based biomarkers is a highly appealing yet difficult-to-realize approach for the early detection of pathological changes, including cancers, infections, or metabolic diseases, such as diabetes. While a major focus of the research community lies on the investigation of pain-free blood sampling and devices for venous blood analysis, menstruation blood remains a largely ignored sampling source. Growing evidence shows excellent correlation between biomarker levels in menstruation blood and venous blood for an entire clinical panel of analytes. Here, we introduce a wearable, microfluidic diagnostic platform integrated into standard hygiene pads for the electronic-free naked eye-readable direct detection of disease biomarkers in menstruation blood (MenstruAI). We demonstrate semi-quantitative biomarker detection from menstruation using infection and inflammation biomarker C-reactive protein (CRP), gynecological cancer biomarkers (CEA and CA-125), and endometriosis biomarker CA-125 as representative examples of relevant proteinaceous biomarkers. The color-changes induced by the presence of these biomarkers can be read-out by the naked eye as well as by a machine-learning algorithm implemented into a smartphone-app, enabling semi-quantitative analysis. The presented MenstruAI platform has the potential to revolutionize women’s health by providing a non-invasive, affordable, and accessible approach to health monitoring, potentially democratizing healthcare by making health services more available and equitable.
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