4.5 Article

Smartphone-based colorimetric ELISA implementation for determination of women's reproductive steroid hormone profiles

期刊

MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
卷 55, 期 10, 页码 1735-1741

出版社

SPRINGER HEIDELBERG
DOI: 10.1007/s11517-016-1605-7

关键词

Enzyme-linked immunosorbent assay (ELISA); Colorimetry; Spectrophotometry; Immunoenzyme techniques; Image processing; Computer-assisted

资金

  1. Natural Sciences and Engineering Research Council of Canada [611184]
  2. Canadian Institutes of Health Research [106705]
  3. Michael Smith Foundation for Health Research

向作者/读者索取更多资源

Biologists frequently collect and analyze biospecimens in naturalistic (i.e., field) conditions to ascertain information regarding the physiological status of their study participants. Generally, field-collected biospecimens need to be stored frozen in the field and then transported frozen to laboratory facilities where traditional biomarker assays, such as enzyme-linked immunosorbent assays (ELISAs), are conducted. As proper storage and transport of frozen specimens is often logistically difficult and expensive, particularly in nonurban field settings, methods that reduce the need for specimen storage and transport would benefit field-research dependent disciplines such as biology, ecology and epidemiology. One limiting factor to running assays in the field is the use of large and expensive equipment to visualize and quantify the assays, such as microplate readers. Here, we describe an implementation of colorimetric ELISA visualization and quantification using two novel and portable imaging instrumentation systems and data processing techniques for the determination of women's reproductive steroid hormone profiles. Using the light absorbance and transmittance properties of the chemical compounds that make up the hormone assay, we were able to estimate unknown hormone concentrations using a smartphone system and a webcam system. These estimates were comparable to those from a standard laboratory multiple reader (smartphone: accuracy = 82.20%, R (2) > 0.910; webcam: accuracy = 87.59%, R (2) > 0.942). This line of applied research, in the long run, is expected to provide necessary information for examining the extent to which reproductive function varies within and between populations and how it is influenced by psychosocial, energetic and environmental challenges. Our validation of these novel, portable visualization and quantification systems allows for the eventual development of a compact and economical closed system which can be used to quantify biomarker concentrations in remote areas.

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