Quantitating ultra-low concentrations of protein biomarkers is critical for early disease diagnosis and treatment. However, most current point-of-care (POC) assays are limited in sensitivity. Herein, we introduce an ultra-sensitive and facile microbubbling assay for the quantification of protein biomarkers with a digital-readout method that requires only a smartphone camera. We used machine learning to develop a smartphone application for automated image analysis to facilitate accurate and robust counting. Using this method, post-prostatectomy surveillance of prostate specific antigen (PSA) can be achieved with a detection limit (LOD) of 2.1 fm (0.060 pg mL-1 ), and early pregnancy detection using βhCG can be achieved with a of 0.034 mIU mL-1 (2.84 pg mL-1 ). This work provides the proof-of-principle of the microbubbling assay with a digital readout as an ultra-sensitive technology with minimal requirement for power and accessories, facilitating future POC applications.
Keyphrases
- high throughput
- high resolution
- machine learning
- protein protein
- prostate cancer
- mass spectrometry
- amino acid
- binding protein
- ms ms
- small molecule
- current status
- single cell
- minimally invasive
- big data
- photodynamic therapy
- liquid chromatography tandem mass spectrometry
- gold nanoparticles
- high performance liquid chromatography