Demonstrates high sensitivity and efficiency in microfluidic analysis for lab-on-a-chip applications, suggesting advancements in point-of-care testing.
Compared to miniaturized microfluidic chips, their supporting equipment tends to be large and bulky. Sometimes, it is not even specifically designed for the microfluidic chips. In this study, we have designed a highly integrated microfluidic analyzer for both chemiluminescence immunoassay and fluorescence loop-mediated isothermal amplification (LAMP) detection with an enhanced cooled CMOS camera. We disassembled the cooled CMOS camera into smaller components for easier integration into the analyzer and improved its cooling module, thereby enabling exposures of up to 180 s without observable thermal noise appearing in the images. The analyzer can detect fluorescence signals from a 2.0 nM fluorescein isothiocyanate (FITC) solution, which demonstrates its high sensitivity. Offering a wide field of view with high definition, this analyzer enables detailed visualization of microfluidic channels, thereby facilitating efficient analysis in lab-on-a-chip applications. The integration of a multibandpass filter enables the analyzer to detect both chemiluminescence and fluorescence signals without filter switching. The high-precision temperature controller installed in the analyzer provides a stable thermal environment for nucleic acid amplification. Both multiplex quantitative chemiluminescence immunoassays and fluorescence LAMP detection can be performed on microfluidic chips with high analytical performance. The built-in 1.8 in. single-board computer controls the camera, temperature controller, and other devices via I/O ports and is itself controlled by a networked tablet computer via wireless connections, which significantly improves the operational convenience. With a volume of 3.78 cubic decimeters and a weight of 1.3 kg, this highly integrated analyzer provides a compact and robust platform for microfluidic chips in laboratories. Furthermore, it has excellent potential for application in point-of-care testing.
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Shen et al. (2026) studied this question.
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