Monitoring of nanodiamonds in human urine using artificial neural networks

Abstract

Phone: þ7 495 939 16 53, Fax: þ7 495 939 11 04This paper presents the results of application of the elaborated methods for monitoring of nanodiamonds in human urine using fluorescence spectroscopy. High efficiency of artificial neural networks applied for recognition and estimation of the concentration of nanodiamonds in urine with a strong autofluorescence background is demonstrated. It was found that minimal concentration of nanodiamonds with strong fluorescence containing nitrogen-vacancy (NV) centers can be detected in urine by fluorescence spectroscopy at a level of 3.06 Â 10 À4 g L À1 ; while use of artificial neural networks for detection of weakly fluorescent detonation nanodiamonds provides reasonably high accuracy of detection, not worse than 6.8 Â 10 À3 g L À1 .

Prospects of Using Machine Learning and Diamond Nanosensing for High Sensitivity SARS-CoV-2 Diagnosis

“…The background autofluorescence can restrain the detection of a biomarker available at low concentrations. Using the inverse problem for the separation of biomarker signal from the background artificial neural network (ANN) algorithm has been tested to determine the concentration of 100 nm FNDs from the samples of human urine [74]. The technique combines Raman and fluorescence spectroscopy to acquire NV emission within the 640-800 nm band.…”

DNA-nanodiamond interactions influence on fluorescence of nanodiamonds

“…The synthesis of the samples is described in [5,6]. We note here that 10 nm DNDs and 5 nm DNDs were treated differently, as the results of which DNDs 5 nm were obtained with much more intense fluorescence (FL) due to production of tiny carbon dots on the DNDs surface [7].…”

“…The Raman spectra and FL spectra of the samples were obtained using a laser spectrometer, as described in [5,6].…”