Methylglyoxal Adducts Levels in Blood Measured on Dried Spot by Portable Near-Infrared Spectroscopy
| Autor: | Natalia Malara, Giuseppe Donato, Maria Laura Coluccio, Nicola Coppedè, Virginia Garo, Marco Flavio Michele Vismara, Francesco Gentile, Giuseppe Bonapace, Patrizio Candeloro |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Chromatography
Chemistry near-infrared spectroscopy General Chemical Engineering Methylglyoxal Near-infrared spectroscopy Vibration absorption Article Adduct methylglyoxal adducts chemistry.chemical_compound secretome Interstitial fluid point-of-care Biological fluids General Materials Science Spectroscopy early cancer detection QD1-999 Whole blood |
| Zdroj: | Nanomaterials, Vol 11, Iss 2432, p 2432 (2021) Nanomaterials Volume 11 Issue 9 |
| ISSN: | 2079-4991 |
| Popis: | The altered glucose metabolism characterising cancer cells determines an increased amount of methylglyoxal in their secretome. Previous studies have demonstrated that the methylglyoxal, in turn, modifies the protonation state (PS) of soluble proteins contained in the secretomes of cultivated circulating tumour cells (CTCs). In this study, we describe a method to assess the content of methylglyoxal adducts (MAs) in the secretome by near-infrared (NIR) portable handheld spectroscopy and the extreme learning machine (ELM) algorithm. By measuring the vibration absorption functional groups containing hydrogen, such as C-H, O-H and N-H, NIR generates specific spectra. These spectra reflect alterations of the energy frequency of a sample bringing information about its MAs concentration levels. The algorithm deciphers the information encoded in the spectra and yields a quantitative estimate of the concentration of MAs in the sample. This procedure was used for the comparative analysis of different biological fluids extracted from patients suspected of having cancer (secretome, plasma, serum, interstitial fluid and whole blood) measured directly on the solute left on a surface upon a sample-drop cast and evaporation, without any sample pretreatment. Qualitative and quantitative regression models were built and tested to characterise the different levels of MAs by ELM. The final model we selected was able to automatically segregate tumour from non-tumour patients. The method is simple, rapid and repeatable moreover, it can be integrated in portable electronic devices for point-of-care and remote testing of patients. |
| Databáze: | OpenAIRE |
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