Intelligent Point-of-Care Biosensing Platform Based on Luminescent Nanoparticles and Microfluidic Biochip with Machine Vision Algorithm Analysis

Abstract

Realizing the point-of-care tumor markers biodetection with good convenience and high sensitivity possesses great significance for prompting cancer monitoring and screening in biomedical study field. Herein, the quantum dots luminescence and microfluidic biochip with machine vision algorithm-based intelligent biosensing platform have been designed and manufactured for point-of-care tumor markers diagnostics. The employed quantum dots with excellent photoluminescent performance are modified with specific antibody as the optical labeling agents for the designed sandwich structure immunoassay. The corresponding biosensing investigations of the designed biodetection platform illustrate several advantages involving high sensitivity (~ 0.021 ng mL^-1), outstanding accessibility, and great integrability. Moreover, related test results of human-sourced artificial saliva samples demonstrate better detection capabilities compared with commercially utilized rapid test strips. Combining these infusive abilities, our elaborate biosensing platform is expected to exhibit potential applications for the future point-of-care tumor markers diagnostic area.

Keywords: Biochip; Biosensing; Luminescent nanoparticles; Machine vision; Point-of-care.

Fig. 1

Schematic diagram of tumor marker detection platform, which consists of saliva sample collection, sandwich-based immunoassay reagents incubation, microfluidic biochip filtration for unconjugated QDs and luminescent images acquired by portable biosensing platform, machine vision algorithm analysis in the cloud, and test results obtained via smartphone

Fig. 2

Investigations of morphology, crystalline structure, surface modification, and QDs luminescent property. a TEM image of core–shell CdSe/ZnS QDs. b HR-TEM images (top) of QDs (scale bar: 10 nm) and relevant inset showing the FFT diffraction pattern (scale bar: 3 nm). STEM images (bottom) under the bright or dark field (scale bar: 5 nm). c XRD spectra of core–shell QDs. d SEM images of PS microspheres with (up) and without (down) CEA protein conjugation. The left side scale bar is 50 μm, and the right side is 10 μm. e Zeta potential histogram of PS microspheres and QDs with and without antibody modification. f PL emission spectrum of QDs under UV (365 nm) excitation. The inset is related optical image of QDs. g Schematic illustration of the luminescent processes for core–shell QDs under UV irradiation

Fig. 3

Filtrated and washable capability of microfluidic biochip and related biosensing properties. a The filtration (top) and cleanable (bottom) performance images of microfluidic biochip (scale bar: 500 μm). b Optical photographs of PS microspheres without (up) and with (down) CEA conjugation (scale bar: 50 μm). c The emission spectra of filtrated PS microspheres connected with QDs with different concentrations of CEA conjugation. d Normalized intensity of microfluidic biochip with various CEA connections and related fitting curves. e The linear relationship for conjugated and separated PS microspheres in microfluidic biochip for CEA protein detection. f Specificity test of CEA detection against related interfering objects

Fig. 4

Machine vision algorithm-based point-of-care intelligent biodetection platform. a Schematic illustration of point-of-care intelligent biosensing platform with various components. b Image recognition workflow of the adopted machine vision algorithm. c The optical pictures of microfluidic biochips in separated zones with different CEA concentrations. d The calculated grayscale (top) and RGB (bottom) intensity for CEA detection via the intelligent biosensing platform. e CIE intensity for this intelligent biosensing system with different CEA concentrations. f Schematic diagram of Bayer filter utilized for CMOS electronic components. g The discrimination values of image recognition and analysis in various color spaces involving CIE space, grayscale, and RGB color

Fig. 5

Detection performance comparison for simulated samples of CEA tumor marker. a Schematic diagram for artificial saliva preparation. b The optical images of two commercial CEA tumor marker test strips including LFA-1 (top) and LFA-2 (bottom). c Histogram plot of related commercial test strips with LFA-1 (up) and LFA-2 (down) by gray values calculated from the selected area. d The column chart of CIE intensity for designed biosensing platform with diverse CEA tumor marker concentrations