Knowledge Management & Discovery Lab, Otto-von-Guericke University, 39106 Magdeburg, Germany.
Department of Experimental Pediatrics, University Hospital, Otto-von-Guericke University, 39120 Magdeburg, Germany.
Sensors (Basel). 2021 Jul 21;21(15):4960. doi: 10.3390/s21154960.
Monitoring the immune system's status has emerged as an urgent demand in critical health conditions. The circulating cytokine levels in the blood reflect a thorough insight into the immune system status. Indeed, measuring one cytokine may deliver more information equivalent to detecting multiple diseases at a time. However, if the reported cytokine levels are interpreted with considering lifestyle and any comorbid health conditions for the individual, this will promote a more precise assessment of the immune status. Therefore, this study addresses the most recent advanced assays that deliver rapid, accurate measuring of the cytokine levels in human blood, focusing on add-on potentials for point-of-care (PoC) or personal at-home usage, and investigates existing health questionnaires as supportive assessment tools that collect all necessary information for the concrete analysis of the measured cytokine levels. We introduced a ten-dimensional featuring of cytokine measurement assays. We found 15 rapid cytokine assays with assay time less than 1 h; some could operate on unprocessed blood samples, while others are mature commercial products available in the market. In addition, we retrieved several health questionnaires that addressed various health conditions such as chronic diseases and psychological issues. Then, we present a machine learning-based solution to determine what makes the immune system fit. To this end, we discuss how to employ topic modeling for deriving the definition of immune fitness automatically from literature. Finally, we propose a prototype model to assess the fitness of the immune system through leveraging the derived definition of the immune fitness, the cytokine measurements delivered by a rapid PoC immunoassay, and the complementary information collected by the health questionnaire about other health factors. In conclusion, we discovered various advanced rapid cytokine detection technologies that are promising candidates for point-of-care or at-home usage; if paired with a health status questionnaire, the assessment of the immune system status becomes solid and we demonstrated potentials for promoting the assessment tool with data mining techniques.
监测免疫系统的状态在危急健康状况下已成为一项迫切需求。血液中循环细胞因子的水平反映了对免疫系统状态的全面了解。事实上，测量一种细胞因子可能会提供更多的信息，相当于一次检测多种疾病。然而，如果考虑到个体的生活方式和任何合并的健康状况来解释报告的细胞因子水平，这将促进对免疫状态的更精确评估。因此，本研究针对目前最先进的快速检测技术，这些技术能够精确测量人类血液中的细胞因子水平，重点研究了在即时护理（PoC）或个人家庭使用方面的附加潜力，并调查了现有的健康问卷，作为支持评估工具，收集所有必要的信息，用于具体分析测量的细胞因子水平。我们引入了细胞因子测量分析的十个维度特征。我们发现了 15 种快速细胞因子分析检测方法，检测时间少于 1 小时；有些可以在未处理的血液样本上运行，而其他的则是成熟的市场上可购买的商业产品。此外，我们还检索了一些针对各种健康状况（如慢性疾病和心理问题）的健康问卷。然后，我们提出了一个基于机器学习的解决方案，以确定是什么使免疫系统健康。为此，我们讨论了如何使用主题建模自动从文献中推导出免疫健康的定义。最后，我们提出了一个原型模型，通过利用快速 PoC 免疫分析提供的细胞因子测量结果以及健康问卷收集的其他健康因素的补充信息，来评估免疫系统的健康状况。总之，我们发现了各种先进的快速细胞因子检测技术，它们是即时护理或家庭使用的有前途的候选者；如果与健康状况问卷配对，免疫系统状态的评估将更加可靠，我们还展示了利用数据挖掘技术来促进评估工具的潜力。
