Dual-Signal Triple-Mode Optical Sensing Platform for Assisting in the Diagnosis of Kidney Disorders.
Xiwen YeDejiang GaoXiaowei MuQiong WuPin-Yi MaDaqian SongPublished in: Analytical chemistry (2023)
As known biomarkers of kidney diseases, N -acetyl-β-d-glucosaminidase (NAG) and β-galactosidase (β-GAL) are of great importance for the diagnosis and treatment of diseases. The feasibility of using multiplex sensing methods to simultaneously report the outcome of the two enzymes in the same sample is even more alluring. Herein, we establish a simple sensing platform for the concurrent detection of NAG and β-GAL using silicon nanoparticles (SiNPs) as a fluorescent indicator synthesized by a one-pot hydrothermal route. p -Nitrophenol (PNP), as a common enzymatic hydrolysis product of the two enzymes, led to the attenuation of fluorometric signal caused by the inner filter effect on SiNPs, the enhancement of colorimetric signal due to the increase of intensity of the characteristic absorption peak at around 400 nm with increasing reaction time, and the changes of RGB values of images obtained through a color recognition application on a smartphone. The fluorometric/colorimetric approach combined with the smartphone-assisted RGB mode was able to detect NAG and β-GAL with good linear response. Applying this optical sensing platform to clinical urine samples, we found that the two indicators in healthy individuals and patients (glomerulonephritis) with kidney diseases were significantly different. By expanding to other renal lesion-related specimens, this tool may show great potentials in clinical diagnosis and visual inspection.
Keyphrases
- high throughput
- gold nanoparticles
- hydrogen peroxide
- living cells
- high resolution
- ejection fraction
- newly diagnosed
- label free
- end stage renal disease
- fluorescent probe
- sensitive detection
- high speed
- prognostic factors
- real time pcr
- deep learning
- squamous cell carcinoma
- quantum dots
- photodynamic therapy
- anaerobic digestion
- nitric oxide
- radiation therapy
- high intensity
- machine learning
- locally advanced
- single molecule
- rectal cancer
- heavy metals
- liquid chromatography
- municipal solid waste