ReactomePA: an R/Bioconductor package for reactome pathway analysis and visualization

Abstract

Iron deficiency, a leading cause of anemia, is one of the globe's top nutritional disorders according to the World Health Organization. Hemochromatosis, on the other hand, is associated to excess iron, and is usually diagnosed late in the stages of irreversible organ damage. Since abnormally low or high blood iron levels are common worldwide and can be of serious detriment to human health, a ubiquitously available technique for measurement of blood iron could represent a substantial improvement in point-of-care medical technology for monitoring iron-related blood disorders and could potentially spark a trend toward proper early prevention of diseases and health maintenance throughout the life span. Here, we introduce a smartphone-based colorimetric detection system for iron measurement in human serum. The system is designed for point-of-care screening and iron monitoring, and was optimized to be low-cost while still allowing for accurate, rapid iron assessment. It employs a dry sensor strip with optimized chemistry in which iron ions are stripped from blood transport proteins, reduced from Fe(III) to Fe(II), and subsequently chelated with ferene, developing a visible color change for smartphone detection of total iron. We compare the common laboratory iron detection assay of human serum to that of our dry sensor strip. The prototype smartphone assay was sensitive to iron detection with a dynamic range of 50 - 300 µg/dL, sensitivity of 0.00047 a.u/µg/dL and coefficient of variation of 10.5% versus the standard lab approach with sensitivity of 0.00091 a.u/µg/dL and coefficients of variation of 2.2%. Further, a detection limit near 15 µg/dL provided by the smartphone system indicated the system's potential capability for detection of iron deficiencies.,Finally, drawn human venous blood sample processed for serum and measured for total iron were simultaneously sent to a commercial testing facility (LabCorp) and processed by the smartphone system, averaging errors of less than 3% around the true value of 231 µg/dL. In addition, spectrophotometric validation of the iron detection kinetics for the test conditions were investigated, rendering a more complete insight of the detection reaction. The new mobile-app based colorimetric assay agreed with the standard spectrophotometric method, and provides promising features of mobility and low-cost manufacturing for global healthcare settings.