prikaz prve stranice dokumenta Nonnegative Least Squares Approach to Quantification of 1H Nuclear Magnetic Resonance Spectra of Human Urine
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Nonnegative Least Squares Approach to Quantification of 1H Nuclear Magnetic Resonance Spectra of Human Urine
Analytical Chemistry, 93 (2020), 2; 745-751. https://doi.org/10.1021/acs.analchem.0c02837
Kopriva, Ivica; Jerić, Ivanka; Popović Hadžija, Marijana; Hadžija, Mirko; Vučić Lovrenčić, Marijana

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Kopriva, I., Jerić, I., Popović Hadžija, M., Hadžija, M. i Vučić Lovrenčić, M. (2020). Nonnegative Least Squares Approach to Quantification of 1H Nuclear Magnetic Resonance Spectra of Human Urine. Analytical Chemistry, 93. (2), 745-751. doi: 10.1021/acs.analchem.0c02837

Kopriva, Ivica, et al. "Nonnegative Least Squares Approach to Quantification of 1H Nuclear Magnetic Resonance Spectra of Human Urine." Analytical Chemistry, vol. 93, br. 2, 2020, str. 745-751. https://doi.org/10.1021/acs.analchem.0c02837

Kopriva, Ivica, Ivanka Jerić, Marijana Popović Hadžija, Mirko Hadžija i Marijana Vučić Lovrenčić. "Nonnegative Least Squares Approach to Quantification of 1H Nuclear Magnetic Resonance Spectra of Human Urine." Analytical Chemistry 93, br. 2 (2020): 745-751. https://doi.org/10.1021/acs.analchem.0c02837

Kopriva, I., et al. (2020) 'Nonnegative Least Squares Approach to Quantification of 1H Nuclear Magnetic Resonance Spectra of Human Urine', Analytical Chemistry, 93(2), str. 745-751. doi: 10.1021/acs.analchem.0c02837

Kopriva I, Jerić I, Popović Hadžija M, Hadžija M, Vučić Lovrenčić M. Nonnegative Least Squares Approach to Quantification of 1H Nuclear Magnetic Resonance Spectra of Human Urine. Analytical Chemistry [Internet]. 07.12.2020. [pristupljeno 25.04.2024.];93(2):745-751. doi: 10.1021/acs.analchem.0c02837

I. Kopriva, I. Jerić, M. Popović Hadžija, M. Hadžija i M. Vučić Lovrenčić, "Nonnegative Least Squares Approach to Quantification of 1H Nuclear Magnetic Resonance Spectra of Human Urine", Analytical Chemistry, vol. 93, br. 2, str. 745-751, Prosinac 2020. [Online]. Dostupno na: https://urn.nsk.hr/urn:nbn:hr:264:969781. [Citirano: 25.04.2024.]

Za citiranje koristite ovu mrežnu adresu: https://urn.nsk.hr/urn:nbn:hr:264:969781
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Naslov (engleski)Nonnegative Least Squares Approach to Quantification of 1H Nuclear Magnetic Resonance Spectra of Human Urine
AutorIvica Kopriva
AutorIvanka Jerić
AutorMarijana Popović Hadžija
AutorMirko Hadžija
AutorMarijana Vučić Lovrenčić
Autorova ustanovaInstitut Ruđer Bošković
Autorova ustanova(Klinička bolnica Merkur)
Znanstveno / umjetničko
područje, polje i grana		BIOMEDICINA I ZDRAVSTVO
Temeljne medicinske znanosti
Znanstveno / umjetničko
područje, polje i grana		PRIRODNE ZNANOSTI
Matematika
Znanstveno / umjetničko
područje, polje i grana		PRIRODNE ZNANOSTI
Kemija
Znanstveno / umjetničko
područje, polje i grana		TEHNIČKE ZNANOSTI
Računarstvo
Sažetak (engleski)
Due to its quantitative character and capability for high throughput screening, 1H nuclear magnetic resonance (NMR) spectroscopy is used extensively in the profiling of biofluids such as urine and blood plasma. However, the narrow frequency bandwidth of 1H NMR spectroscopy leads to a severe overlap of the spectra of components present in the complex mixtures such as biofluids. Therefore, 1H NMR-based metabolomics analysis is focused on targeted studies related to concentrations of the small number of metabolites. Here, we propose a library-based approach to quantify proportions of overlapping metabolites from 1H NMR mixture spectra. The method boils down to the linear nonnegative least squares (NNLS) problem, whereas proportions of the pure components contained in the library stand for the unknowns. The method is validated on an estimation of the proportions of: (i) the 78 pure spectra, presumably related to type 2 diabetes mellitus (T2DM), from their synthetic linear mixture ; (ii) metabolites present in 62 1H NMR spectra of urine of subjects with T2DM and 62 1H NMR spectra of urine of control subjects. In both cases, the in-house library of 210 pure components 1H NMR spectra represented the design matrix in related NNLS problem. The proposed method pinpoints 63 metabolites that in a statistically significant way discriminate T2DM group from the control group, and 46 metabolites discriminating control from the T2DM group. For several T2DM- discriminative metabolites, we prove their presence by an independent analytical determination or by pointing out the corresponding findings in the published literature.
Ključne riječi (engleski)
Jezikengleski
Vrsta publikacijeZnanstveni rad - Izvorni znanstveni rad
Status objaveObjavljen
Vrsta recenzijeRecenziran - međunarodna recenzija
Verzija publikacijeObjavljena verzija rada (izdavačev PDF)
Naslov časopisaAnalytical Chemistry
Brojčani podacivol. 93, br. 2, str. 745-751
p-ISSN0003-2700
e-ISSN1520-6882
DOIhttps://doi.org/10.1021/acs.analchem.0c02837
URN:NBNurn:nbn:hr:264:969781
Datum objave elektroničkog izdanja2020-12-07
ProjektŠifra: IP-2016-06-5235
Naziv (hrvatski): Strukturne dekompozicije empirijskih podataka za računalno potpomognutu dijagnostiku bolesti
Kratica: DEDAD
Voditelj: Ivica Kopriva
Pravna nadležnost: Hrvatska
Financijer: HRZZ - Hrvatska zaklada za znanost
Linija financiranja: 594.400,00 HRK
URL dokumentahttps://pubs.acs.org/doi/10.1021/acs.analchem.0c02837
Vrsta resursaTekst
Prava pristupaOtvoreni pristup
Uvjeti korištenjaIkona licence Imenovanje-Nekomercijalno-Bez prerada 4.0 međunarodna (CC BY-NC-ND 4.0)
Datum i vrijeme pohrane2021-07-07 09:16:26