Details

Autor(en) / Beteiligte

• Caixeta, Douglas Carvalho
• Lima, Cassio
• Xu, Yun
• Guevara-Vega, Marco
• Espindola, Foued Salmen
• Goodacre, Royston
• Zezell, Denise Maria
• Sabino-Silva, Robinson

Titel

Monitoring glucose levels in urine using FTIR spectroscopy combined with univariate and multivariate statistical methods

Ist Teil von

• Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy, 2023-04, Vol.290, p.122259, Article 122259

Ort / Verlag

England: Elsevier B.V

Erscheinungsjahr

2023

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• [Display omitted] •Urinary spectral of FTIR with univariate and multivariate statistical can use for diabetes surveillance.•Spectral of urine analysis exhibited consistent changes related to urea, creatinine, and glucose.•The 100 % accuracy of glucose (1074 cm−1) and strong correlation with glycosuria can discriminate the urine of diabetics.•MCR-ALS analysis suggested that glucose prediction could be helpful in the screening and monitoring of diabetes. The development of novel platforms for non-invasive continuous glucose monitoring applied in the screening and monitoring of diabetes is crucial to improve diabetes surveillance systems. Attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy of urine can be an alternative as a sustainable, label-free, fast, non-invasive, and highly sensitive analysis to detect changes in urine promoted by diabetes and insulin treatment. In this study, we used ATR-FTIR to evaluate the urinary components of non-diabetic (ND), diabetic (D), and diabetic insulin-treated (D + I) rats. As expected, insulin treatment was capable to revert changes in glycemia, 24-h urine collection volume, urine creatinine, urea, and glucose excretion promoted by diabetes. Several differences in the urine spectra of ND, D, and D + I were observed, with urea, creatinine, and glucose analytes being related to these changes. Principal components analysis (PCA) scores plots allowed for the discrimination of ND and D + I from D with an accuracy of ∼ 99 %. The PCA loadings associated with PC1 confirmed the importance of urea and glucose vibrational modes for this discrimination. Univariate analysis of second derivative spectra showed a high correlation (r: 0.865, p < 0.0001) between the height of 1074 cm-1 vibrational mode with urinary glucose concentration. In order to estimate the amount of glucose present in the infrared spectra from urine, multivariate curve resolution-alternating least square (MCR-ALS) was applied and a higher predicted concentration of glucose in the urine was observed with a correlation of 78.9 % compared to urinary glucose concentration assessed using enzyme assays. In summary, ATR-FTIR combined with univariate and multivariate chemometric analyses provides an innovative, non-invasive, and sustainable approach to diabetes surveillance.