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Recent advances in lab-on-paper diagnostic devices using blood samples.

Wen-Chin LeeHwee-Yeong NgChih-Yao HouChien-Te LeeLung-Ming Fu
Published in: Lab on a chip (2021)
Lab-on-paper, or microfluidic paper-based analytical devices (μPADs), use paper as a substrate material, and are patterned with a system of microchannels, reaction zones and sensing elements to perform analysis and detection. The sample transfer in such devices is performed by capillary action. As a result, external driving forces are not required, and hence the size and cost of the device are significantly reduced. Lab-on-paper devices have thus attracted significant attention for point-of-care medical diagnostic purposes in recent years, particularly in less-developed regions of the world lacking medical resources and infrastructures. This review discusses the major advances in lab-on-paper technology for blood analysis and diagnosis in the past five years. The review focuses particularly on the many clinical applications of lab-on-paper devices, including diabetes diagnosis, acute myocardial infarction (AMI) detection, kidney function diagnosis, liver function diagnosis, cholesterol and triglyceride (TG) analysis, sickle-cell disease (SCD) and phenylketonuria (PKU) analysis, virus analysis, C-reactive protein (CRP) analysis, blood ion analysis, cancer factor analysis, and drug analysis. The review commences by introducing the basic transmission principles, fabrication methods, structural characteristics, detection techniques, and sample pretreatment process of modern lab-on-paper devices. A comprehensive review of the most recent applications of lab-on-paper devices to the diagnosis of common human diseases using blood samples is then presented. The review concludes with a brief summary of the main challenges and opportunities facing the lab-on-paper technology field in the coming years.
Keyphrases
  • healthcare
  • type diabetes
  • metabolic syndrome
  • emergency department
  • mass spectrometry
  • sickle cell disease
  • left ventricular
  • adipose tissue
  • data analysis