Abstract：
Universal health care is attracting increased attention nowadays, because of the large increase in population all over the world, and a similar increase in life expectancy, leading to an increase in the incidence of non-communicable (various cancers, coronary diseases, neurological and old-age-related diseases) and communicable diseases/pandemics like SARS-COVID 19. This has led to an immediate need for a healthcare technology that should be cost-effective and accessible to all. A technology being considered as a possible one at present is liquid biopsy, which looks for markers in readily available samples like body fluids which can be accessed non- or minimally- invasive manner. Two approaches are being tried now towards this objective. The first involves the identification of suitable, specific markers for each condition, using established methods like various Mass Spectroscopy techniques (Surface-Enhanced Laser Desorption/Ionization Mass Spectroscopy (SELDI-MS), Matrix-Assisted Laser Desorption/Ionization (MALDI-MS), etc., immunoassays (Enzyme-Linked Immunoassay (ELISA), Proximity Extension Assays, etc.) and separation methods like 2-Dimensional Polyacrylamide Gel Electrophoresis (2-D PAGE), Sodium Dodecyl-Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE), Capillary Electrophoresis (CE), etc. In the second approach, no attempt is made the identification of specific markers; rather an efficient separation method like High-Performance Liquid Chromatography/ Ultra-High-Performance Liquid Chromatography (HPLC/UPLC) is used to separate the protein markers, and a profile of the protein pattern is recorded, which is analysed by Artificial Intelligence (AI)/Machine Learning (MI) methods to derive characteristic patterns and use them for identifying the disease condition. The present report gives a summary of the current status of these two approaches and compares the two in the use of their suitability for universal healthcare.
摘要：
如今，全民医疗保健正引起越来越多的关注，由于全世界人口的大量增加，和预期寿命的类似增长，导致非传染性疾病(各种癌症，冠状动脉疾病,神经系统和老年相关疾病）和传染病/大流行，如SARS-COVID19。这导致迫切需要一种具有成本效益且所有人都可以使用的医疗保健技术。目前被认为是可能的技术是液体活检，其在容易获得的样品如体液中寻找标记物,其可以非侵入性或最小侵入性方式获得。目前正在为实现这一目标尝试两种方法。首先涉及合适的识别，每个条件的特定标记，使用已建立的方法，如各种质谱技术（表面增强激光解吸/电离质谱（SELDI-MS），基质辅助激光解吸/电离(MALDI-MS),等。,免疫测定(酶联免疫测定(ELISA)，邻近延伸测定，等。)和二维聚丙烯酰胺凝胶电泳(二维PAGE)等分离方法，十二烷基硫酸钠聚丙烯酰胺凝胶电泳(SDS-PAGE),毛细管电泳(CE),等。在第二种方法中，没有尝试进行特定标记的鉴定;而高效液相色谱/超高效液相色谱（HPLC/UPLC）等有效的分离方法用于分离蛋白质标记，并记录蛋白质模式的轮廓，通过人工智能（AI）/机器学习（MI）方法进行分析，以得出特征模式并将其用于识别疾病状况。本报告总结了这两种方法的现状，并比较了这两种方法在全民医疗保健中的适用性。
